Providing an experience-focused navigation session

Abstract

A computing device may implement a method for providing an experience-focused navigation session. The method includes obtaining user data corresponding to a user of the computing device and a current location of the user. The method further includes determining a semantic mapping corresponding to the user based on one or more user preferences and a location history included in the user data, and determining a suggested experience-focused navigation session for the user based on the semantic mapping and the current location of the user. The suggested experience-focused navigation session includes an ordered list of one or more suggested points of interest. The method further includes automatically providing the suggested experience-focused navigation session to the user as an appointment on the computing device.

Description

[Technical field]

[0001] TECHNICAL FIELD The present disclosure relates to navigation sessions, and more particularly, to techniques for providing experience-focused navigation sessions to users. [Background technology]

[0002] The background discussion provided herein is intended to provide a general context for the present disclosure. The work of the inventors named herein to the extent described in this Background section, and aspects of the description that may not otherwise qualify as prior art at the time of filing, are not admitted explicitly or implicitly as prior art to the present disclosure.

[0003] Today, many users request navigation guidance to guide the user to a desired destination. A variety of software applications are available that can provide step-by-step navigation instructions and may run on computers, smartphones, devices integrated into vehicles, etc. In many scenarios, a user may utilize these navigation applications to guide himself or herself to points of interest (POIs) that the user may not otherwise be able to find. For example, a user visiting a new city may have specific POIs that he or she would like to visit during the trip and may utilize one of the navigation applications to guide himself or herself to the specific POIs.

[0004] However, in many cases, users may not know of POIs that may interest them in a particular location, and / or these users may need additional activities to fill their schedule during a particular time period. Although conventional navigation applications may provide users with the opportunity to search more generally, such as "Italian restaurants" or "nearby theaters," when no clear POI is known, these services still require the user to understand and specify what they are looking for in order for the application to return meaningful recommendations. Furthermore, conventional navigation applications typically cannot provide collateral / accompanying recommendations that provide the user with any type of schedule of activities related to the user's search and / or interests. As a result, the user is left to search for activities that may interest the user on their own, creating a poor user experience and expending a significant amount of time and energy.

[0005] Thus, typically, conventional navigation applications are unable to automatically provide users with POI recommendations that are specifically tailored to the user without any prompting, and any recommendations made by these conventional applications fail to take into account the holistic nature of such recommendations. Summary of the Invention [Means for solving the problem]

[0006] Using the techniques of the present disclosure, the user's computing device may automatically generate and inform the user of an experience-focused navigation session that may seamlessly guide the user to multiple points of interest (POIs). The experience-focused navigation session may generally navigate the user to one or more POIs in a predefined and / or dynamic order by providing continuous navigation guidance for the user to follow. Each of the experience-focused navigation sessions may be dynamically created so that they are fully customized to each user, and / or the experience-focused navigation session may have an open agenda for a given time frame at a specific location. In either case, the experience-focused navigation session may be created and / or enhanced by the user answering some questions generated by the present technology. For example, the system of the present disclosure may generate and / or utilize a chatbot interface to obtain information from the user in an intuitive manner. Regardless, user input may act as feedback from which the systems of the present disclosure may learn to improve experience-focused navigation sessions and experience-focused navigation session recommendations for the user and other users who employ these technologies.

[0007] In general, a POI may be a landmark, a business, a street, a road, a highway, a town, a public transportation hub, a body of water, a shopping center, a department store, a neighborhood, a building, a house, a restaurant, and / or any other suitable location, or any combination thereof. The POIs referred to herein may be proximate (e.g., within a few miles) to the user's current location and may be identified as a result of user preferences (e.g., favorite restaurants, daytime activities, nighttime activities, etc.) and / or any other suitable criteria and output to the user in suggested experiences. For example, a suggested experience may include hiking a popular trail and having dinner at an Italian restaurant as a result of the user's explicit and / or inferred interest in both activities.

[0008] The user's location history may be used to determine which POIs the user liked in the past in order to suggest similar ones for new locations. The system of the present disclosure may infer from signals such as future calendar events or real-time GLS tracks whether the user is in a local town or traveling. If the user is traveling, the system of the present disclosure may further consider the purpose of the trip (e.g., business / vacation / family reunion / etc.) and whether the destination is a new destination or a previously visited destination. For a new city, the system of the present disclosure may suggest tourist attractions such as Pike Place Market and the Space Needle for Seattle. However, the system of the present disclosure may omit such tourist attractions for locations the user has previously visited.

[0009] For example, a user may prefer a quiet experience, or alternatively a very busy and bustling set of destinations. The system of the present disclosure can accommodate either of these desires by accessing relevant historical and real-time information for individual POIs to generate an experience-focused navigation session that is tailored to the individual user.

[0010] In certain aspects, the system of the present disclosure may be integrated with a calendar application so that the user can know in advance of the appointments that are planned. The user may have one or more destinations to visit on a particular day. In this case, the system of the present disclosure may dynamically generate an experience-focused navigation session by filling one or more time slots with other matching destinations. For example, a user may be skiing during the day and watching a show at night, with a gap between them. To fill this gap, the system of the present disclosure may recommend restaurants that fit the overall feel of the user's activity and fit within the time and space constraints already established by the destinations selected by the user.

[0011] These calendar entries that are suggestions from the system of the present disclosure may then be surfaced on the calendar application of the user's computing device as "faux commitments" that are displayed in faded colors and / or otherwise indicated. Such entries may be accepted or rejected according to the user's interest in the suggestions, and these acceptances and / or rejections may be used by the system of the present disclosure to refine subsequent recommendations. In this manner, the user may be passively guided into an experience-focused navigation session, as no user interaction is required other than the up-to-date calendar and an accept / reject / ignore interface response (or lack thereof).

[0012] Additionally, for any given experience-focused navigation session accepted by a user, the system of the present disclosure may track the user's progress during that experience-focused navigation session (subject to the user's opt-in) and derive various indications of satisfaction with the experience-focused navigation session based on the user's behavior. For example, if the user follows a recommended experience, the system may ask the user to explicitly rate the experience-focused navigation session (e.g., on a scale of 1 to 10) on one or more dimensions, such as cost, quality, entertainment value, appropriateness, etc. The system of the present disclosure may utilize these rankings to highlight good experience-focused navigation sessions, which may then be recommended to other users.

[0013] In certain cases, the system of the present disclosure may infer an implicit cue of satisfaction based on several behaviors including (i) not visiting one or more of the one or more suggested points of interest, (ii) visiting an alternative point of interest instead of one of the one or more suggested points of interest, or (iii) receiving a rejection indication from the user of a suggested experience-focused navigation session. The system of the present disclosure may attempt to identify historical "ad hoc" experience-focused navigation sessions and request that the user rank those ad hoc experience-focused navigation sessions to determine whether the ad hoc experience-focused navigation sessions should be officially recognized / recommended experience-focused navigation sessions.

[0014] Additionally, experience-focused navigation sessions can be tagged so that the type of experience-focused navigation session (e.g., party, relaxing, educational, etc.) can be discovered by other users. The system of the present disclosure may enable experience-focused navigation sessions to be shared on social media, sent to other users, commented on, etc., to increase the overall popularity of the experience-focused navigation session. Additionally or alternatively, merchants / venues / etc. may collaborate to produce their experience-focused navigation sessions, which may include some discounts and other cost savings as a result of visiting their POIs as part of the experience-focused navigation session. For example, tickets to a particular venue may have a QR code that, when scanned by a user, opens a navigation application with a particular "recommended" experience-focused navigation session, where the next stop then offers a 20% discount for three hours, and visiting a subsequent stop may result in a 25% discount at the POI.

[0015] In this manner, aspects of the present disclosure provide a technical solution to the problem of erroneous and / or otherwise low-quality recommendations from navigation / map software by automatically providing an experience-focused navigation session to a user. Conventional systems may provide guidance to a single POI upon a user's request, and at best may be able to provide guidance to multiple POIs, but typically fail to understand why such POIs may be shown together. As a result, conventional systems fail to allocate an appropriate amount of time for each shown POI, fail to suggest and / or otherwise determine alternative POI possibilities for contingencies, and generally lack the ability to treat an input sequence of visits as a holistic experience. As a result, conventional systems typically require a user to independently determine POIs and interact with a navigation / map application multiple times to receive guidance from one POI to the next. In contrast, the experience-focused navigation session of the present disclosure eliminates the need for repetitive and tedious interactions with a navigation application by providing a seamless user experience to reliably travel from one point of interest to another in a time frame that guarantees an enjoyable experience at each location.

[0016] One exemplary embodiment of the techniques of this disclosure is a method for providing an experience-focused navigation session, the method including: obtaining, in one or more processors of a computing device, user data corresponding to a user of the computing device and a current location of the user; determining, by the one or more processors, a semantic mapping corresponding to the user based on one or more user preferences and a location history included in the user data; determining, by the one or more processors, a suggested experience-focused navigation session for the user based on the semantic mapping and the current location of the user, the suggested experience-focused navigation session including an ordered list of one or more suggested points of interest; and automatically providing, by the one or more processors, the suggested experience-focused navigation session to the user as an appointment on the computing device.

[0017] Another exemplary embodiment is a computing device for providing an experience-focused navigation session. The computing device includes one or more processors and a non-transitory computer-readable memory coupled to the one or more processors and storing instructions that, when executed by the one or more processors, cause the computing device to: obtain user data corresponding to a user of the computing device and the user's current location, determine a semantic mapping corresponding to the user based on one or more user preferences and a location history included in the user data, determine a suggested experience-focused navigation session for the user based on the semantic mapping and the user's current location, where the suggested experience-focused navigation session includes an ordered list of one or more suggested points of interest, and automatically provide the suggested experience-focused navigation session to the user as a notification on the computing device.

[0018] Yet another example embodiment is a tangible, non-transitory computer-readable medium storing instructions for providing an experience-focused navigation session, the instructions, when executed by one or more processors, causing the one or more processors to obtain user data corresponding to a user of a computing device and the user's current location, determine a semantic mapping corresponding to the user based on one or more user preferences and location history included in the user data, determine a suggested experience-focused navigation session for the user based on the semantic mapping and the user's current location, where the suggested experience-focused navigation session includes an ordered list of one or more suggested points of interest, and automatically provide the suggested experience-focused navigation session to the user as a notification on the computing device.

[0019] Yet another exemplary embodiment of the techniques of this disclosure is a method for navigating a user to a point of interest. The method may include, in one or more processors of a computing device, obtaining user data corresponding to a user of the computing device and a current location of the user, determining, by the one or more processors, a semantic mapping corresponding to the user based on one or more user preferences and a location history included in the user data, and determining, by the one or more processors, a proposed navigation session for the user based on the semantic mapping and the current location of the user. The proposed navigation session may include an ordered list of one or more proposed points of interest. The method may include providing, by the one or more processors, the proposed navigation session to the user, for example, as an appointment on the computing device. The method may include receiving a user selection of a proposed navigation session, and navigating the user to the one or more proposed points of interest of the proposed navigation session. [Brief description of the drawings]

[0020] [Figure 1] FIG. 1 is a block diagram of an example communication system in which techniques for providing an experience-focused navigation session may be implemented. [Diagram 2] 1A-1C illustrate exemplary transitions between a navigation display and a calendar application display corresponding to a proposed experience-focused navigation session. [Diagram 3] 1 illustrates an example transition between an appointment notification generated using techniques of this disclosure and a display of a navigation session that focuses on the experience of using a navigation application. [Figure 4A]1 illustrates an example navigation application display that requests various user feedback to enhance and / or otherwise tailor an experience-focused navigation session. [Figure 4B] 1 illustrates an example navigation application display that requests various user feedback to enhance and / or otherwise tailor an experience-focused navigation session. [Figure 4C] 1 illustrates an example navigation application display that requests various user feedback to enhance and / or otherwise tailor an experience-focused navigation session. [Diagram 5] FIG. 2 illustrates an exemplary calendar application display as a result of a user scanning a coded indicia. [Figure 6] 1 illustrates an exemplary navigation application display as a result of a user scanning a coded indicia. [Figure 7] 2 is a flow diagram of an example method for providing an experience-focused navigation session that may be implemented in a computing device such as the computing device of FIG. 1 . DETAILED DESCRIPTION OF THE PREFERRED EMBODIMENTS

[0021] overview As referred to herein, an "experience" (also referred to herein as a "suggested experience" and an "experience-focused navigation session") may generally refer to a sequence of POIs that logically fit together into an extended navigation session. More specifically, an "experience" may be recommended to or requested by a user, and directions to each of the POIs may be displayed to the user in a navigation application as a unit such that the user may receive turn-by-turn directions to each POI as part of the sequence during the navigation session. For example, a particular experience may include turn-by-turn directions to a first location (and the navigation application may display turn-by-turn directions to the first location), and the user may stay in the first location for two hours. After the two hours have elapsed, the navigation application may display turn-by-turn directions to a second location that is included as part of the particular experience, and the user may remain in the second location for one hour until the navigation application recommends that the user can proceed to a third location. In this way, the navigation application may display navigation directions to each POI in sequence so that the user may proceed to each individual location as part of a larger, unique experience designed to appeal to the user's desires (e.g., a night out, visiting historical architecture, etc.).

[0022] In general, the user's computing device may generate experience recommendations including at least one POI for the user based on the user data and the user's current location. The experience recommendations may include navigation instructions to each of the POIs included as part of the experience recommendation, and may be scheduled so that the user receives notifications (and guidance) to move from one POI to the next at appropriate time intervals. For example, the user may arrive in a new city, and the techniques of this disclosure may automatically generate several experience recommendations, each including at least one POI, for the user based on the user's data and the user's current location within the new city. The user's data may indicate that the user frequently visits seafood restaurants and jazz clubs in a local town, and as a result, the techniques of this disclosure may generate an experience recommendation featuring seafood restaurants and jazz clubs in the new city for the user to experience. This experience recommendation may be automatically uploaded as an appointment to a calendar application of the user's computing device, and the user may choose to accept or decline the appointment. If the user accepts the appointment, the calendar application may instruct and / or otherwise cause the navigation application to provide directions from the user's current location to the seafood restaurant at the time of the appointment. After a certain period of time and / or upon prompting from the user (e.g., after a meal), the navigation application may then provide directions from the seafood restaurant to a jazz club. Once all planned POIs and / or all POIs the user intends to visit have been visited, the navigation application may also provide directions back to the user's accommodations (e.g., the user's home, hotel, etc.). Thus, the user may be automatically and seamlessly guided through a navigation session focused on an experience specifically tailored to the user preferences and location.

[0023] In this manner, aspects of the present disclosure provide a technical solution to the problem of disjointed, limited, and / or otherwise inappropriate navigation / POI recommendations by determining a semantic mapping corresponding to a user, generating a proximity value for an experience-focused navigation session, and automatically providing the suggested experience-focused navigation session to the user as an appointment on a calendar application of the user's computing device. For example, the user computing device may determine the semantic mapping based on user preferences and the user's location history, which may be included as part of the user data. Furthermore, the user computing device may utilize a trained experiential learning model to generate a proximity value based on the user's semantic mapping and current location, and may communicate with a remote navigation server to obtain a navigation route and associated route data corresponding to the suggested experience-focused navigation session. In this manner, the user computing device may generate and provide to the user a specifically adapted experience that eliminates subsequent searches by the user, thereby reducing network traffic and correspondingly increasing available bandwidth.

[0024] Additionally, the technology improves the overall user experience of utilizing navigation applications and, more broadly, traveling to and from POIs. The technology automatically determines navigation sessions that focus on experiences specifically tailored / curated to user preferences. This helps to provide a more user-friendly and relevant experience that enhances user satisfaction with the user's trip / social plans and reduces user confusion and frustration resulting from disjointed, limited (e.g., a single place recommendation in response to a user prompt), and / or otherwise inappropriate navigation / POI recommendations from traditional navigation applications. Additionally, experiences may be curated by a large number of connected users (e.g., users of navigation applications who rate each POI) such that each experience is more likely to be safe and enjoyable. Thus, the technology enables safer, more user-specific, and more enjoyable navigation sessions to POIs.

[0025] Exemplary Hardware and Software Components 1, an example communication system 100 in which the techniques of this disclosure may be implemented includes a user computing device 102. The user computing device 102 may be, for example, a portable device such as a smartphone or tablet computer. The user computing device 102 may also be a laptop computer, a desktop computer, a personal digital assistant (PDA), a wearable device such as a smart watch or smart glasses, or the like. In some embodiments, the user computing device 102 may be removably attached to a vehicle, may be integrated into the vehicle, and / or may be capable of interacting with a vehicle's head unit to provide navigation instructions.

[0026] The user computing device 102 may include one or more processors 104 and a memory 106 that stores machine-readable instructions executable on the processor 104. The processor 104 may include one or more general-purpose processors (e.g., CPUs) and / or special-purpose processing units (e.g., graphics processing units (GPUs)). The memory 106 may optionally be non-transitory memory and may include one or more suitable memory modules, such as random access memory (RAM), read-only memory (ROM), flash memory, other types of persistent memory, etc. The memory 106 may store instructions for implementing a navigation application 108 that may provide navigation guidance (e.g., by displaying guidance or issuing voice instructions via the user computing device 102), display interactive digital maps, request and receive routing data for providing driving, walking, or other navigation guidance, provide various geo-located content such as traffic, points of interest (POI), and weather information, etc.

[0027] Further, the navigation application 108 may include an experiential learning model 120 configured to implement and / or support the techniques of the present disclosure for providing an experience-focused navigation session. That is, the experiential learning model 120 may generate proximity values ​​corresponding to experience-focused navigation sessions for the user based on the semantic mapping and the user's current location. In some scenarios, the experiential learning model 120 may be a machine learning model trained using training semantic data and training location data as inputs to output proximity values ​​corresponding to multiple experiences, as described further herein. Furthermore, the experiential learning model may be a long short-term memory (LSTM) model, and in certain aspects may utilize the user's calendar data to generate the proximity values.

[0028] 1 illustrates the navigation application 108 as a standalone application, the functionality of the navigation application 108 may be provided in the form of an online service accessible via a web browser running on the user computing device 102, provided as a plug-in or extension to another software application running on the user computing device 102, etc. In general, the navigation application 108 may be provided in different versions for different operating systems. For example, a manufacturer of the user computing device 102 may provide a software development kit (SDK) that includes the navigation application 108 for the Android™ platform, another SDK for the iOS™ platform, etc.

[0029] The memory 106 may also store an operating system (OS) 110, which may be any type of suitable mobile or general-purpose operating system. The user computing device 102 may further include a global positioning system (GPS) 112 or another suitable positioning module, a network module 114, a user interface 116 for displaying map data and guidance, and an input / output (I / O) module 118. The network module 114 may include one or more communication interfaces, such as an interface hardware, software, and / or firmware for enabling communication over a cellular network, a Wi-Fi network, or any other suitable network, such as a network 144 discussed below. The I / O module 118 may include I / O devices capable of receiving input from and presenting output to the surrounding environment and / or the user. The I / O module 118 may include a touch screen, a display, a keyboard, a mouse, buttons, keys, a microphone, a speaker, and the like. In various embodiments, the user computing device 102 may include fewer components than those shown in FIG. 1, or conversely, additional components.

[0030] The user computing device 102 may communicate with the navigation server 150 via a network 144. The network 144 may include one or more of an Ethernet-based network, a private network, a cellular network, a local area network (LAN), and / or a wide area network (WAN) such as the Internet. The navigation application 108 may receive map data, navigation directions, and other geolocation content from the navigation server 150. Additionally, the navigation application 108 may access map, navigation, and geolocation content stored locally on the user computing device 102 and may access the navigation server 150 periodically to update local data or during navigation to access real-time information, such as real-time traffic data.

[0031] In certain aspects, the network 144 may include any communication link suitable for short-range communication and may conform to a communication protocol such as, for example, Bluetooth™ (e.g., BLE), Wi-Fi (e.g., Wi-Fi Direct), NFC, ultrasonic signals, etc. Additionally or alternatively, the network 144 may be, for example, a Wi-Fi, a cellular communication link (e.g., conforming to 3G, 4G, or 5G standards), etc. In some scenarios, the network 144 may also include a wired connection.

[0032] Navigation server 150 includes one or more processors 152 and memory 153 that stores computer-readable instructions executable by processor 152. Memory 153 may store experiential learning model 154 similar to experiential learning model 120. Experiential learning model 154 may support similar functionality to experiential learning model 120 from the server side and may facilitate generation of proximity values ​​as described herein. For example, user computing device 102 may provide user data and the user's current location to navigation server 150 and request that experiential learning model 154 generate a proximity value.

[0033] Generally, the user computing device 102 may communicate with the navigation server 150 to obtain navigation directions to each of the POIs included as part of the proposed experience. The navigation server 150 may generally optimize routes between the user's current location and each POI based on current traffic conditions, weather conditions, user preferences (e.g., avoid highways, avoid narrow roads, avoid tolls, etc.), and / or any other suitable information. Each of these user preferences may be stored on the user computing device 102 and / or the navigation server 150. In any event, when the navigation server 150 has generated at least one route from the user's current location to a POI, the server 150 may transmit the route over the network 144 back to the user computing device 102 for display and / or further adjustment by the device 102 and / or the user.

[0034] Of course, route optimization may include any number of user preferences, contextual indications, and / or any other suitable metrics. For example, if a user intends to travel from point A to point B, and a first route from point A to point B includes toll roads and some private roads, and a second route includes only public roads, and the user has expressed a preference (e.g., via the navigation application 108) to avoid non-public roads, the route is optimized by generating a second route and corresponding navigation instructions for display to the user. The navigation server 150 may generate both routes and may send both routes to the user computing device 102 for consideration, with the second route shown as the primary route and the first route shown as a secondary / alternate route. Additionally, the user computing device 102 and / or the user may select a particular navigation route received from the navigation server 150 depending on which available route has a faster estimated arrival time, has fewer turns, has a shorter distance, requires fewer tolls, faces less traffic, passes through more points of interest, etc.

[0035] The experiential learning model 154 and the experiential learning model 120 together can operate as components of an experience-focused navigation system. Alternatively, the entire functionality of the experiential learning model 154 can be implemented in the experiential learning model 120.

[0036] In any case, the navigation server 150 may be communicatively coupled to various databases, such as a map database 155, a traffic database 157, and a points of interest (POI) database 159, from which the navigation server 150 may retrieve navigation-related data. The map database 155 may include map data such as map tiles, visual maps, road geometry data, road type data, speed limit data, etc. The traffic database 157 may store historical and real-time traffic information. The POI database 159 may store descriptions, locations, images, and other information relating to landmarks or points of interest. Although FIG. 1 shows databases 155, 157, and 159, the navigation server 150 may be communicatively coupled to additional or conversely fewer databases. For example, the navigation server 150 may be communicatively coupled to a database that stores weather data.

[0037] Example display during a scenario involving an experience-focused navigation session Techniques of the present disclosure for providing an experience-focused navigation session are discussed below with reference to the displays shown in Figures 2-6. Throughout the description of Figures 2-6, actions described as being performed by the user computing device 102 may, in some embodiments, be performed by the navigation server 150, or may be performed in parallel by the user computing device 102 and the navigation server 150. For example, either the user computing device 102 and / or the navigation server 150 may utilize the experiential learning models 120, 154 to generate a proximity value corresponding to the experience-focused navigation session.

[0038] 2, the user computing device 102 may implement a navigation application 108 and display a graphical user interface (GUI) 204 of the navigation application 108. The navigation application 108 may also display a notification 206 somewhere within the GUI 204 informing the user that the user computing device 102 may have generated suggested experiences for the user. For example, the user may be utilizing the navigation application 108 to identify where the user is currently located within an unfamiliar city, and the user computing device 102 may generate one or more suggested experiences for the user to consider. While the navigation application 108 is active and the user is viewing the GUI 204, the user computing device 102 may display the notification 206 to allow the user to interact with the notification and consider the suggested experiences. However, it should be understood that the user may be using any application stored on the user computing device 102 and / or may not currently be using the computing device 102 at all, and the device 102 may push a notification 206 to the user (e.g., by an audible sound, buzzer, etc.) to inform the user of the proposed experience.

[0039] In any event, as shown in FIG. 2, the user may interact with the notification 206 (e.g., by tapping, clicking, swiping, etc.) and the user computing device 102 may transition between the navigation application 108 and the calendar application 202. The calendar application 202 may generally include appointments at corresponding times during which the user intends to perform, attend, and / or otherwise participate in the scheduled activity represented by the respective appointment. The calendar application 202 may render a GUI 210 that displays the user's calendar and the user's appointments for a displayed time period. The calendar application 202 may, for example, display all appointments currently scheduled for the user for a particular month (e.g., November as shown in FIG. 2), and the calendar application 202 may include as part of the GUI 210 a first appointment 212 that corresponds to the proposed experience.

[0040] The user computing device 102 is configured to request the user's permission to access the user's calendar data and / or any other application or data therein. For example, when the user interacts with the notification 206, the user computing device 102 may prompt the user to approve access to the user's calendar application / data. In response to receiving the user's approval, the user computing device 102 may proceed to access the user's calendar data, transition between the navigation application 108 and the calendar application 202, place an appointment (e.g., the first appointment 212) in the user's calendar, and / or any other suitable action, or combination thereof.

[0041] The suggested experience may include the POIs, directions to each of the POIs, a duration to be spent performing the suggested experience, an approximate time spent at each of the POIs, and / or any other suitable information, or combinations thereof. Thus, the user computing device 102 may prompt the user with a notification 206 and may await user interaction with the notification 206. In response to receiving the user's interaction with the notification 206, the user computing device 102 may place a first appointment 212 in the user's calendar and transition from the navigation application 108 to the calendar application 202 to display the GUI 210. The first appointment 212 may be a tentative appointment such that the user may have to explicitly accept the first appointment 212 in order for the calendar application 202 to provide subsequent reminders, alerts, and / or any other suitable functionality corresponding to the activity represented by the first appointment 212. However, in certain aspects, the calendar application 202 may place the first appointment 212 on the user's calendar without requiring explicit acceptance from the user. If the user accepts the first appointment 212 anyway, the calendar application 202 may provide the user with subsequent reminders, alerts, updates, and / or other suitable information as the appointment approaches. Additionally, upon arrival of the time indicated by the first appointment 212, the user computing device 102 may automatically activate the navigation application 108 to provide turn-by-turn guidance to a POI that is included as part of the proposed experience, as described herein.

[0042] Of course, if the user declines the first appointment 212, the calendar application 202 may remove the first appointment 212 from the user's calendar. In this scenario, the user computing device 102 may cause the calendar application 202 to provide the user with another suggested experience with a second appointment (not shown), which may feature a different POI, a different suggested date / time, a different allocation of time for each POI, and / or any other suitable difference, or combination thereof. In certain aspects, the user computing device 102 may initially suggest multiple suggested experiences to the user upon receiving the user's interaction with the notification 206, and may allow the user to review the line-up of experiences to determine a preferred experience. Furthermore, in some aspects, the user computing device 102 may automatically upload tentative and / or non-tentative appointments representing experiences to the user's calendar application 202 without receiving the user's interaction with the notification 206.

[0043] As an example, a user may arrive in an unfamiliar city for vacation on Friday afternoon with the intention of exploring the unfamiliar city over the weekend. The user may open the user computing device 102 and may open the navigation application 108 to learn the user's current location (e.g., an airport) in the unfamiliar city. The user computing device 102 may receive the user's current location and compare the current location with the user's location history to determine that the user is in a new location. The user computing device 102 may also access the user's purchase history and location history to identify user preferences related to activities / experiences. Additionally, the user computing device 102 may access the calendar application 202 and determine that a vacation status ranging from Friday afternoon to Sunday afternoon indicates that the user is going to a new location on vacation.

[0044] Using this location data, calendar data, and user preference data, the user computing device 102 (e.g., at least in part through the experiential learning model 120) may determine a suggested experience for the user on Saturday afternoon. The suggested experience may include multiple POIs in an unfamiliar city, and may allocate ample time at each POI to allow the user to fully experience each POI before moving on to the next POI. When the allocated time for a particular POI has elapsed, the navigation application 108 may prompt the user to determine whether the user is willing to move on to the next POI, and in response to receiving a positive indication from the user, the navigation application 108 may automatically provide turn-by-turn guidance from the current POI to the subsequent POI. After the user has finished visiting some / all of the POIs included as part of the suggested experience, the navigation application 108 may also provide turn-by-turn guidance to return the user to the user's accommodations (e.g., hotel, rented house, etc.).

[0045] As previously mentioned, the user computing device 102 may provide the notification 206 to the user while the user is viewing the navigation application 108 and / or at any other suitable time, such as when the user is not utilizing the user computing device 102. Figure 3 illustrates an exemplary appointment notification 302 on a home screen GUI 304 that the user computing device 102 may generate regardless of whether the user is currently viewing and / or otherwise using the user computing device 102. Additionally, Figure 3 illustrates a transition between the home screen GUI 304 and a navigation session display 310 that focuses on the experience of using the navigation application 108.

[0046] The user computing device 102 may generate an appointment notification 302 in response to determining that a proposed experience is about to begin. The user computing device 102 may push the appointment notification 302 to the home screen GUI 304 to remind the user about a previously accepted or tentative proposed experience and to inform the user that the proposed experience will begin in a particular period of time (e.g., 5 minutes, 15 minutes, 1 hour, etc.). The appointment notification 302 may include a brief description of the proposed experience (e.g., "A Fun Night in Chicago") and may further indicate when (date / time) the proposed experience is scheduled to begin (e.g., October 6, 2021). However, it should be understood that the appointment notification 302 may include any suitable information, such as the POIs included in the proposed experience, the time assigned to each POI, addresses of some / all of the POIs, directions to the POIs, and / or any other suitable information, or combinations thereof.

[0047] In general, the appointment notification 302 may act as both a reminder for the user and a selectable indication to initiate an experience-focused navigation session. Thus, when the user interacts with the appointment notification 302 and / or when the start time indicated in the notification 302 arrives, the user computing device 102 may transition from the home screen GUI 304 to an experience-focused navigation session display 310 rendered by the navigation application 108. If the home screen GUI 304 is locked, the user computing device 102 may prompt the user to enter access credentials to authorize the user and then transition from the GUI 304 to the experience-focused navigation session display 310.

[0048] In any case, when the user computing device 102 transitions from the home screen GUI 304 to the experience-focused navigation session display 310, the navigation application 108 may cause the display 310 to provide the user with turn-by-turn navigation directions to the POIs included as part of the experience-focused navigation session. More specifically, the user computing device 102 may initiate a first navigation session that utilizes the navigation application 108 to provide a first set of navigation instructions from an origin to a destination (e.g., a first POI). The first set of navigation instructions may include turn-by-turn directions for reaching the first POI along a first route. During the first navigation session, the user computing device 102 may display, via an experience-focused navigation session display 310, a map showing the location of the user computing device 102, the heading of the user computing device 102, an estimated time of arrival, an estimated distance to the first POI, an estimated time to the first POI, current navigation directions, one or more future navigation directions of the first set of navigation instructions, one or more user-selectable options for changing the view or adjusting the navigation directions, etc. The user computing device 102 may also issue audio instructions corresponding to the first set of navigation instructions.

[0049] When the user completes the first set of navigation instructions, the user may arrive at the first POI, and the user computing device 102 may log the user's arrival time. The user computing device 102 may track the amount of time the user spends at the first POI and may suggest that the user proceed to the second POI after the amount of time allocated to the first POI has elapsed. For example, the first POI may be a restaurant and the second POI may be a movie theater. The suggested experience may allocate two hours to the first POI to allow the user to enjoy a meal at the restaurant, after which the user computing device 102 may prompt the user with a notification to determine whether the user is ready to travel to the movie theater. In response to receiving a positive response from the user, the user computing device 102 may initiate a second navigation session utilizing the navigation application 108 to provide a second set of navigation instructions from the starting point (e.g., the first POI) to the destination (e.g., the second POI). With the exception of turn-by-turn guidance that guides the user to the second POI along the second route, the second navigation session may be similar to the first navigation session, and the second set of navigation instructions may provide the user with similar information and options to interact with the instructions as the first set of navigation instructions. When the user arrives at the second POI, the user computing device 102 may log the user's arrival time, and the device 102 may perform an analysis similar to that already described to determine when to provide a third navigation session to a third POI, a fourth navigation session to a fourth POI, and so on.

[0050] Of course, if the user dismisses the notification to travel from the first POI to the second POI, the user computing device 102 may postpone providing the second navigation session until the user indicates that he is ready to travel to the second POI. For example, the two hours allotted in the proposed experience may not be enough to fully enjoy a meal at a specified restaurant (e.g., the first POI). As a result, after two hours have passed since the user arrived at the restaurant, the user may not be ready to travel to the second POI. The user may dismiss the notification to start the second navigation session and continue to enjoy the user's dining experience at the first POI, and may spontaneously start the second navigation session at any time after the meal is over.

[0051] In some aspects, the user computing device 102 may suggest an alternative POI if a particular proposed POI as part of the proposed experience is not accepted by the user. Continuing with the above example, a second POI included as part of the user's proposed experience may include a particular movie playing at a particular time so that the user can travel from the first POI with enough time to catch the particular movie showing. However, if the user takes significantly more time than originally allocated by the user computing device 102 to enjoy a meal at a restaurant (first POI), by the time the user is ready to travel to the second POI, the movie may already have started and the user may not be able to enter the theater. Thus, the user computing device 102 may analyze the user preference data, the current location, and the current time to determine an alternative proposed experience that fits into the user's updated schedule. The user computing device 102 may inform the user that the movie has started and therefore the originally intended trip to the second POI (the movie theater) may not be enjoyable, and the device 102 may additionally provide notification of alternative experiences that the user may have time for and be interested in based on user preferences indicated in the user data.

[0052] To better appreciate the updates and notifications provided by the user computing device 102, FIGS. 4A-4C illustrate displays of an exemplary navigation application that requests various user feedback to enhance and / or otherwise tailor an experience-focused navigation session. As previously described, the suggested experiences include turn-by-turn guidance to each POI included in the schedule of the suggested experiences, and the user computing device 102 may request user input when activating the navigation application 108 and determining whether to provide guidance to the user. Additionally, when the user computing device 102 determines that the user may want to proceed from a first POI to a second POI, the device 102 may prompt the user to provide an input indicating such. Thus, as shown in FIG. 4A, the user computing device 102 may render a GUI 402 via the navigation application 108 to provide a prompt 404 to the user. Additionally or alternatively, the user computing device 102 may determine that the time allotted to the first POI has elapsed and may provide a prompt 404 to the user through a locked home screen (e.g., the home screen GUI 302).

[0053] Regardless, once the user receives the prompt 404, the user may interact with the prompt 404 by pressing, clicking, tapping, swiping, etc., one of the interactive buttons 406a, 406b. If the user selects the yes interactive button 406a, the user computing device 102 may instruct the navigation application 108 to generate and display on the GUI 402 turn-by-turn navigation directions from the first POI to the second POI. If the user selects the no interactive button 406b, the user computing device 102 may determine alternative experience and / or POI suggestions to replace the second POI and / or the remainder of the proposed experience for the user's consideration if the user is not interested in proceeding with the proposed experience.

[0054] As an example, a user may be visiting a museum, and at the end of the time allotted to the museum in the schedule of suggested experiences, the user computing device 102 may prompt the user to proceed to the next POI, which may be a local bistro for lunch. The user may decide that they are not interested in a local bistro and would instead like to have a quick coffee at a nearby cafe. The user may select the No interactive button 406b and proceed to the nearby cafe. The user computing device 102 may analyze the user's current location and determine that the user is currently at a nearby cafe and that it is likely that the user no longer needs a dining-related experience. As a result, the user computing device 102 may suggest experiences that target alternative activities that may interest the user after eating at the cafe, such as a walking tour of a city's historic district or a boutique shopping location.

[0055] When a user completes a portion of a proposed experience, the user computing device 102 may request feedback from the user to assess the level of interest / satisfaction with a particular POI and / or the overall proposed experience. Using this feedback, the user computing device 102 may enhance the overall experience by determining whether a particular POI should be included in a particular experience and / or which experiences should be suggested to a particular user, as discussed herein. For example, as shown in FIG. 4B, the navigation application 108 may instruct the user computing device 102 to display a GUI 412 featuring guidance to second, third, and / or other subsequent POIs after at least a first POI included as part of the proposed experience.

[0056] The user computing device 102 may cause the navigation application 108 to render and / or otherwise independently render a prompt 414 intended to collect user feedback regarding the previous POI the user has just experienced. The prompt 414 includes four interactive buttons 414a, 414b, 414c, 414d that allow the user to provide various forms of feedback regarding the previous POI. In particular, the good interactive button 414a may allow the user to provide a positive review / feedback regarding the previous POI, the fair interactive button 414b may allow the user to provide an average review / feedback regarding the previous POI, the poor interactive button 414c may allow the user to provide a negative review / feedback regarding the previous POI, and the extra feedback interactive button 414d may allow the user to provide additional feedback regarding the previous POI.

[0057] For example, a user may visit a first POI as part of a proposed experience and may not enjoy the experience. When the user leaves the first POI, the user computing device 102 may provide a prompt 414 to the user to allow the user to provide feedback regarding the first POI, and the user may select the bad interactive button 414c. The user computing device 102 may receive this input and utilize it to further analyze the inclusion of the first POI as part of the proposed experience and / or more generally as a POI recommended for any / all experiences. Additionally, the user computing device 102 may provide the user with a fillable text box in which the user may provide comments related to the user's selection of the bad interactive button 414c. Any comments provided by the user may be received by the user computing device 102 and used, for example, to display to future users of the proposed experience and provide future users with additional information related to the first POI. The user computing device 102 may forward all received comments (whether anonymized or not) to the first POI (e.g., a computing terminal associated with the first POI) to enable employees / administrators / owners of the first POI to read the comments, respond if possible, adjust their practices accordingly, and / or otherwise interpret the information contained in the comments.

[0058] As another example, a user may visit a first POI and a second POI as part of a proposed experience, and the user may determine that the second POI should be proposed as the first POI and the first POI should be the second POI. The user may have enjoyed the second POI anyway, and therefore the user may select both the good interactive button 414a and the additional feedback interactive button 414d to leave a comment indicating as such. The user's selection of the good interactive button 414a may indicate that the second POI provided the user with a high quality experience, and the user may provide a comment after selection of the additional feedback interactive button 414d explaining that the proposed experience would have been improved overall if the second POI and the first POI had been scheduled in the reverse order. Thus, feedback provided by the user after selecting the additional feedback interactive button 414d may not necessarily be made in a negative light toward the second POI (e.g., affecting the rating of the second POI as part of the overall catalogue of experiences), but may be used by the user computing device 102 to determine a more optimal combination of suggested experiences including the first POI and the second POI.

[0059] To that end, the user may wish to provide feedback regarding the proposed experience as a whole in addition to or as opposed to POI-specific feedback. The user may provide such comments during the proposed experience, for example, using the additional feedback interactive button 414d. Additionally or alternatively, the user computing device 102 may provide the user with an opportunity to provide broad feedback related to the proposed experience as a whole after visiting each POI included in the proposed experience's schedule.

[0060] 4C, the navigation application 108 may instruct the user computing device 102 to display a GUI 422 that characterizes the user's current location after some / all of the POIs that are included as part of the proposed experience. The user computing device 102 may cause the navigation application 108 to render and / or otherwise independently render a prompt 424 that is intended to gather user feedback regarding the proposed experience that the user has just experienced. The prompt 424 includes four interactive buttons 424a, 424b, 424c, 424d that allow the user to provide various forms of feedback regarding the proposed experience. In particular, the good interactive button 424a may enable the user to provide a positive review / feedback regarding the proposed experience, the fair interactive button 424b may enable the user to provide an average review / feedback regarding the proposed experience, the bad interactive button 424c may enable the user to provide a negative review / feedback regarding the proposed experience, and the location-specific feedback interactive button 424d may enable the user to provide additional location-specific and / or other feedback regarding the proposed experience.

[0061] As an example, a user may participate in a proposed experience, and after the user completes the activities scheduled as part of the proposed experience, the user computing device 102 may provide the user with a prompt 424 requesting feedback on the user's overall experience. The user may feel that the proposed experience was satisfactory, but that the time allotted at each POI was not sufficient to facilitate a fully enjoyable experience at each POI. Thus, the user may select the so-so interactive button 424b. Selection of the so-so interactive button 424b may enable the user to provide additional comments regarding their impressions of the proposed experience, and may enable the user computing device 102 to upload these comments to a central server (e.g., the navigation server 150) for storage. Selection of the so-so interactive button 424b, together with the comments, may be utilized by the central server to update a rating associated with the proposed experience and provide insights associated with the proposed experience to subsequent users of the proposed experience. Subsequent users may then receive the proposed experience on their computing devices, may read comments from the users related to insufficient time allocation, and may decide to remove the POI from the schedule of the proposed experience in order to enable them to achieve a better experience at the remaining POIs.

[0062] In certain instances, a user may not receive suggested experiences because they are in their local area (e.g., the user's city / town / village) and / or may have deactivated the service on their computing device. However, in these cases, the user may wish to extend their experience by traveling to a POI and traveling to a subsequent POI. For example, a user may go out to lunch on the weekend within a local city and may wish to travel to a subsequent location to participate in an engaging activity. To help the user search for such activities, the POI may include scannable indicia that may activate suggested experiences for the user including subsequent activities that the user may want to participate in after visiting the POI.

[0063] Continuing with the previous example, as shown in FIG. 5, a user out to lunch in a local city may spot a scannable indicia 504 (e.g., a quick response (QR) code) at a restaurant and may capture an image of the scannable indicia 504 with the user computing device 102. The user computing device 102 may decode a payload contained in the scannable indicia 504, which may instruct the device 102 to generate an appointment 508 on the user's calendar 506 in the calendar application 202. The appointment 508 may be and / or otherwise include a suggested experience related to the restaurant where the user is located and where he or she scanned the scannable indicia 504. For example, the appointment 508 may be scheduled to begin shortly after the user scans the indicia 504 and may include a scheduled stop at an art gallery located a few blocks away from the restaurant. Once the user accepts the appointment 508 and the scheduled start time arrives, the calendar application 202 may instruct the navigation application 108 to begin a navigation session with turn-by-turn directions to the art gallery.

[0064] As part of the association of the restaurant and art gallery through the proposed experience in the previous example, a user may benefit from traveling between the restaurant and the art gallery as a result of scanning the scannable indicia 504. For example, in some cases, the art gallery and the restaurant may enter into a reciprocal arrangement that provides patrons of those establishments with a discounted price when participating in an experience offered as a result of scanning the scannable indicia 504. That is, a user who has lunch at the restaurant, scans the scannable indicia 504, and then proceeds to the art gallery and is able to generate a corresponding code or indicia indicative of the user's scan of the indicia 504 at the restaurant may receive a discounted price for admission to the art gallery.

[0065] In this way, the POIs involved in these experiences may receive increased business from users who are directed to those POIs' facilities from the associated facilities, and users may receive attractive discounts and / or other rewards for visiting these POIs in addition to participating in a generally engaging and enjoyable experience. Of course, in certain circumstances, the POIs included in a proposed experience may be landmarks, historical sites, parks, and / or other locations that do not directly involve businesses. In these circumstances, benefits associated with travel between the landmark POI and the business POI may extend in only one direction (e.g., a discount associated with travel from the landmark POI to the business POI).

[0066] In any event, when the user scans the scannable indicia 504 and the appointment 508 is placed on the user's calendar, the user may choose to accept or reject the appointment 508. If the user rejects the appointment 508, the user computing device 102 may provide an alternative suggested experience, as described above, and / or may simply remove the appointment 508 from the user's calendar. However, if the user accepts the appointment 508, the navigation application 108 may display turn-by-turn directions to the next POI at the scheduled start time of the experience. Additionally or alternatively, the user may scan the scannable indicia 504, which may cause the navigation application 108 to automatically open and provide turn-by-turn directions to the next POI.

[0067] For example, as shown in FIG. 6, a user may scan / image a scannable indicia 602 with a user computing device 102. As a result, the payload of the scannable indicia 602 may cause the navigation application 108 to open and automatically display a GUI 604 featuring turn-by-turn directions to the subsequent POI. As the user navigates to the subsequent POI, the user computing device 102 may display a feedback option for the user to review the previous POI, similar to the prompt 414 of FIG. 4B, even though the user has not navigated to the previous POI as part of the proposed pre-planned experience. Additionally, as the user proceeds to each POI included as part of the experience from the scannable indicia 602, the device 102 may prompt the user for feedback related to each POI, and the device 102 may also prompt the user for feedback corresponding to the experience as a whole, similar to the prompt 424 of FIG. 4C. Using this feedback, individual POIs may evaluate the effectiveness of their experiences and whether to adjust the experience in some way (e.g., partnering with another establishment for a more profitable experience).

[0068] Additionally or alternatively, the user computing device 102 may detect whether another device near the user computing device 102 is participating in an experience and whether it requests an experience from another device. For example, while a user is out with a friend, the friend may select a suggested experience and actively participate in the suggested experience. The user may want to see the suggested experience on his / her device and may request that the friend's device share the suggested experience with the user's device. The friend may accept the user's request, and the friend's device may send a signal including the suggested experience to the user's device. The user may then tap, click, swipe, etc. on the notification to activate the suggested experience within a navigation application, and the user's device may then automatically display turn-by-turn directions, a list of POIs included in the schedule, and / or any other suitable information related to the suggested experience.

[0069] In some scenarios, the user computing device 102 may attempt to discover experiences from other devices only if an interoperability feature of the navigation application 108 is triggered. Generally, the interoperability feature may be triggered manually by the user or may be triggered as a default option. Regardless, the user computing device 102 may detect in various ways whether another device in the vicinity of the first device is conducting an experience-focused navigation session. In some implementations, the user computing device 102 may detect that a nearby computing device is conducting an experience-focused navigation session by receiving an indication in a broadcast over a communication link (e.g., the network 144) from the nearby computing device. For example, the nearby computing device may broadcast that the nearby computing device is currently conducting an experience-focused navigation session. The user computing device 102 may broadcast a request to join the experience-focused navigation session to nearby computing devices such that the nearby computing devices may be able to discover the user computing device 102 over the communication link.

[0070] As a more detailed example, a nearby computing device may broadcast (e.g., a discoverable message) according to a protocol such as Bluetooth™ that a user is currently engaged in an experience-focused navigation session. The nearby computing device may encode the message with the identity of the nearby computing device, and the message may include an indication that the nearby computing device may share the experience-focused navigation session with the user computing device 102. The user computing device 102 may monitor for discoverable devices on a frequency associated with the protocol. After detecting a nearby computing device, the user computing device 102 may provide the identity of the user computing device 102 to the nearby computing device along with a request to obtain the experience-focused navigation session. In response, the nearby computing device may return a signal including access to the experience-focused navigation session, thereby enabling the user computing device 102 to access the experience-focused navigation session.

[0071] Exemplary logic for providing an experience-focused navigation session 7 is a flow diagram illustrating an example method for providing an experience-focused navigation session in accordance with the techniques of this disclosure. For ease of discussion only, it should be understood that the “user computing device” discussed herein with reference to FIG. 7 may correspond to the user computing device 102.

[0072] 7, the method 700 may be performed by a user computing device (e.g., user computing device 102). The method 700 may be implemented in a set of instructions stored on a computer-readable memory and executable on one or more processors (e.g., processor 104) of the user computing device.

[0073] At block 702, one or more processors of the user computing device may obtain user data corresponding to a user of the computing device and the user's current location. In certain aspects, the user data may include timing data including at least one of (i) time of year data, (ii) day of the week data, or (iii) time of day data. For example, the user data may indicate that a user is in a particular location at noon on a Friday in mid-fall. The user's current location may include a city or county, and a specific address or an approximate location, such as near the Louvre Museum in Paris, France.

[0074] At block 704, one or more processors of the user computing device may determine a semantic mapping corresponding to the user based on one or more user preferences and a location history included in the user data. In a particular aspect, the one or more user preferences correspond to a purchasing history of the user, and the location history includes one or more locations visited by the user. For example, the one or more user preferences may indicate that the user usually shops at antique stores and that the user usually travels to popular tourist attractions in various locations. As a result, the user computing device may determine that the user's semantic mapping should correspond to antiques and popular tourist attractions when utilizing the semantic mapping to determine a suggested experience-focused navigation session for the user.

[0075] More generally, generating a semantic mapping may include a user computing device and / or other suitable processing device distilling / reducing information included as part of one or more user preferences and the user's location history into a set of concepts that broadly describe the user's interests. As another example, one or more user preferences may indicate that the user frequently purchases artwork and pizza, and that the user has visited local blues bars, museums, and Italian restaurants in various locations different from the user's home city / town. One or more processors of the user computing device may use this overall information to generate a semantic mapping that heavily features art, food, and music. For each of these categories, the semantic mapping may further include subcategories that refer to particular types of artworks that the user enjoys (e.g., watercolor, oil painting, impressionist, abstract, Renaissance, etc.), particular types of food that the user enjoys (e.g., pizza, Italian, etc.), and / or particular types of music that the user enjoys (e.g., blues, pop, R&B, soul, classical, etc.), so long as such information is included as part of one or more user preferences and the user's location history.

[0076] Thus, using the semantic mapping, the user computing device (e.g., experiential learning model 120) may determine how likely a particular experience is to match the user's interests based on the degree of similarity the particular experience has to the user's semantic mapping. Referring to the previous example, a particular experience may include tags indicating that the particular experience involves stopping by an Italian restaurant with very high reviews for pizza followed by going to a local movie theater for a movie about blues musicians. The user computing device may analyze the particular experience and determine that the user is likely to enjoy this experience because the user's semantic mapping includes references to food (particularly Italian and pizza) as well as music (particularly blues). If the movie playing at the movie theater instead focused on pop musicians, the user computing device may still interpret the experience as one that the user may be interested in doing because the movie may include tags relating it to music, which is also included in the user's semantic mapping (at a broader level than blues music). However, in this case, movies about pop musicians may receive a lower correlation value (eg, confidence score) than movies about blues musicians because the user's semantic mapping matches movies about blues musicians more closely.

[0077] At optional block 706, the user computing device may utilize the experiential learning model to generate a proximity value corresponding to each experiential-focused navigation session of the one or more experiential-focused navigation sessions for the user based on the semantic mapping and the user's current location. The experiential learning model may be a machine learning (ML) model, a rule-based model, and / or any other suitable type of model, or a combination thereof. The proximity value may generally correspond to how closely a particular experiential-focused navigation session correlates with the semantic mapping and the user's current location.

[0078] More specifically, the experiential learning model may utilize various contextual parameters to correlate each experience-focused navigation session to the semantic mapping and the user's current location. For example, the experiential learning model may analyze contextual parameters from the experience-focused navigation sessions that indicate (1) the experience is in Paris, (2) the experience is four hours long, and (3) the experience includes live music and touring historical architecture. Further, the experiential learning model may analyze corresponding contextual parameters from the semantic mapping and the user's current location that indicate (1) the user is in Paris, (2) the user typically goes out for less than three hours at a time before returning home, and (3) the user rarely listens to live music and does not touring historical architecture. The contextual parameters may also indicate that (4) a weather forecast corresponding to the area covered by the experience is predicted to include rain during the scheduled time at the POI, and (5) multiple vehicles currently traveling a portion of the navigation route between two POIs are reporting heavy traffic.

[0079] In the previous example, the model may apply weighting factors to the context parameters to enable a more accurate representation of the semantics of the context parameters. That is, the model may apply a larger weighting factor to the context parameters (1), (2), and (3) than to the parameters (4) and (5) because the parameters (1), (2), and (3) have similar semantic mapping and parameters to the user's current location. Furthermore, if the event taking place at the POI is indoors and therefore not affected by rain, the model may apply a much smaller weighting factor to the parameter (4) to reduce the effect of the parameter (4) on the resulting proximity value corresponding to the experience-focused navigation session. The model may associate an overall lack of interest in experiences over time (e.g., context parameter (2)) together with an overall lack of interest in the planned activity (e.g., context parameter (3)) as an increased likelihood that the user will not accept the experience-focused navigation session. Furthermore, the model may associate a long period of heavy traffic travel to reach the next POI (e.g., context parameter (5)) with an even higher likelihood that the user will not embrace an experience-focused navigation session.

[0080] Overall, the model may apply weighting factors to all or some of the context parameters (1)-(5) to reduce / increase the influence of the context parameters on the resulting proximity values ​​of the experience-focused navigation session. The user computing device may then evaluate all the generated proximity values ​​for the experience-focused navigation session to determine a proposed experience-focused navigation session. That is, the user computing device may determine that the proposed experience-focused navigation session should include activities in Paris that do not last more than three hours and that include activities of interest to the user (e.g., not live music or historical architecture touring).

[0081] In some embodiments, the experiential learning model is a machine learning model trained using the training semantic data and the training location data as inputs to output proximity values ​​corresponding to a plurality of experiences. For example, the experiential learning model may be a long short-term memory (LSTM) model. In these embodiments, the first computing device may include a machine learning engine for training the experiential learning model, and / or the user computing device may include a pre-trained experiential learning model. The machine learning engine may train the experiential learning model using various machine learning techniques, such as regression analysis (e.g., logistic regression, linear regression, or polynomial regression), k-nearest neighbors, decision trees, random forests, boosting (e.g., extreme gradient boosting), neural networks, support vector machines, deep learning, reinforcement learning, Bayesian networks, etc. The experiential learning model may utilize any standard technique, such as an LSTM model, and / or any other suitable machine learning model, such as a linear regression model, a logistic regression model, a decision tree, a neural network, a hyperplane, and / or any combination thereof.

[0082] More specifically, to train the experiential learning model, the machine learning engine may receive training data including multiple sets of training semantic data and training location data corresponding to multiple users and multiple proximity values ​​corresponding to the multiple sets of training semantic data and training location data. Although the training data discussed herein includes multiple sets of training semantic data and training location data corresponding to multiple users and multiple proximity values, this is merely an example for ease of explanation. The training data may include any number of sets of training semantic data and training location data corresponding to multiple users (e.g., additional users utilizing aspects of the present disclosure) and proximity values.

[0083] Additionally, while generating the proximity values ​​has been described in the context of a machine learning environment, it should be understood that generating the proximity values ​​may occur without a machine learning process. For example, a user computing device may determine the proximity values ​​based on a relational database, weighting logic, heuristic rules, grammars, and / or any other suitable algorithmic architecture.

[0084] In certain aspects, the user computing device may receive, at one or more processors, user feedback corresponding to the completion of at least a portion of the suggested experience-focused navigation session. Additionally, the user computing device may train an experiential learning model with the user feedback to provide better, more accurate proximity values, e.g., by one or more processors utilizing a machine learning engine.

[0085] In some aspects, the user data corresponding to the user may include the user's calendar data, and the experiential learning model may generate the proximity value based on the semantic mapping, the user's current location, and the user's calendar data. In these aspects, the user computing device may automatically provide the user, via one or more processors, with a navigation session focused on the suggested experience as an appointment on a calendar application of the computing device.

[0086] In block 708, the user computing device may determine a suggested experience-focused navigation session for the user based on the semantic mapping and the user's current location. The suggested experience-focused navigation session may include an ordered list of one or more suggested points of interest, allowing the user to determine which POIs are included and whether the user is interested in visiting / participating in the activities represented therein. For example, the user computing device may analyze the proximity values ​​generated by the experiential learning model and determine that the experience-focused navigation session with the highest corresponding proximity value should be the suggested experience-focused navigation session.

[0087] In block 710, the user computing device may automatically provide the suggested experience-focused navigation session to the user as an appointment on the computing device by one or more processors. In a particular aspect, the suggested experience-focused navigation session includes (i) an ordered list of one or more suggested points of interest and (ii) sequential navigational guidance to each of the suggested points of interest on the ordered list. Additionally, the suggested experience-focused navigation session may include a start time, and the user computing device may receive, by a user interface of the computing device in one or more processors, an acceptance indication from the user to confirm acceptance of the suggested experience-focused navigation session. When the start time is reached, the user computing device may automatically provide, by one or more processors, sequential navigational guidance on a navigation application of the computing device to guide the user to each of the one or more suggested points of interest on the ordered list. Additionally or alternatively, the user computing device may receive a Quick Read (QR) code scanned by the user at the first location. In response to receiving the QR code, the user computing device may determine a navigation session focused on the suggested experiences, and the ordered list may include (i) at least a second location and (ii) sequential navigation directions from the first location to the second location.

[0088] In some aspects, the user computing device may determine, by one or more processors, one or more indications of satisfaction corresponding to the user not completing a portion of the proposed experience-focused navigation session. Generally, the one or more indications of satisfaction may include (i) not visiting one or more of the one or more suggested points of interest, (ii) visiting an alternative point of interest instead of one of the one or more suggested points of interest, and / or (iii) receiving a rejection indication from the user of the proposed experience-focused navigation session. The user computing device may then, by one or more processors, combine each of the one or more indications of satisfaction with a satisfaction index value and assign the satisfaction index value to the proposed experience-focused navigation session.

[0089] In certain aspects, the user computing device may, via one or more processors, tag the suggested experience-focused navigation session with one or more tags indicative of the type of experience. In these aspects, the user computing device may, via one or more processors, upload the suggested experience-focused navigation session with the one or more tags to a social media platform for sharing the suggested experience-focused navigation session with other users. For example, the user computing device may assign tags indicative of "music" and "cheap" to a particular experience-focused navigation session and upload the particular experience-focused navigation session to a social media platform (e.g., Facebook, Twitter, Instagram, etc.) in an attempt to share the particular experience-focused navigation session with users of the social media platform who may be interested in such experiences.

[0090] Additional Considerations The following additional considerations apply to the above discussion: Throughout this specification, components, operations, or structures described as a single instance may be implemented by multiple instances. Although individual operations of one or more methods are shown and described as separate operations, one or more of the individual operations may be performed simultaneously, and the operations need not be performed in the order shown. Structures and functions presented as separate components in example configurations may be implemented as combined structures or components. Similarly, structures and functions presented as a single component may be implemented as separate components. These and other changes, modifications, additions, and improvements are within the scope of the subject matter of the present disclosure.

[0091] Additionally, certain embodiments are described herein as including logic or certain components, modules, or mechanisms. A module may constitute either a software module (e.g., code stored on a machine-readable medium) or a hardware module. A hardware module is a tangible unit that can perform certain operations and may be configured or arranged in a certain way. In an exemplary embodiment, one or more computer systems (e.g., standalone client or server computer systems) or one or more hardware modules of a computer system (e.g., a processor or group of processors) may be configured by software (e.g., an application or a portion of an application) as a hardware module that operates to perform certain operations as described herein.

[0092] In various embodiments, a hardware module may be implemented mechanically or electronically. For example, a hardware module may include dedicated circuitry or logic that is permanently configured (e.g., as a dedicated processor such as a field programmable gate array (FPGA) or application specific integrated circuit (ASIC)) to perform certain operations. A hardware module may also include programmable logic or circuitry that is temporarily configured by software to perform certain operations (e.g., as contained within a general purpose processor or other programmable processor). It will be appreciated that the decision to implement a hardware module mechanically, in dedicated permanently configured circuitry, or in temporarily configured circuitry (e.g., configured by software) may be driven by cost and time considerations.

[0093] Thus, the term hardware should be understood to encompass tangible entities that are physically constructed, permanently configured (e.g., hardwired), or temporarily configured (e.g., programmed) to operate in a particular manner or perform particular operations described herein. As used herein, a "hardware-implemented module" refers to a hardware module. Given an embodiment in which the hardware modules are temporarily configured (e.g., programmed), each of the hardware modules need not be configured or instantiated at all times. For example, if the hardware modules include a general-purpose processor that is configured using software, the general-purpose processor may be configured as each different hardware module at different times. Thus, the software may, for example, configure the processor to configure a particular hardware module at one time and configure a different hardware module at a different time.

[0094] A hardware module can provide information to and receive information from other hardware. Thus, the described hardware modules may be considered to be communicatively coupled. When multiple such hardware modules are present simultaneously, communication may be achieved through the transmission of signals (e.g., via appropriate circuits and buses) connecting the hardware modules. In embodiments in which multiple hardware modules are configured or instantiated at different times, communication between such hardware modules may be achieved, for example, through the storage and retrieval of information in a memory structure that can be accessed by the multiple hardware modules. For example, one hardware module may perform an operation and store the output of that operation in a memory device to which it is communicatively coupled. An additional hardware module may then access the memory device at a later time to retrieve and process the stored output. A hardware module may also initiate communication with an input or output device and may operate on a resource (e.g., a collection of information).

[0095] Method 700 may include one or more function blocks, modules, individual functions, or routines in the form of tangible computer-executable instructions stored in a computer-readable storage medium, optionally a non-transitory computer-readable storage medium, and executed using a processor of a computing device (e.g., a server device described herein, a personal computer, a smartphone, a tablet computer, a smartwatch, a mobile computing device, or other client computing device). Method 700 may be included, for example, as part of any back-end server (e.g., a map data server described herein, a navigation server, or any other type of server computing device), as a module of a client computing device of the exemplary environment, or as part of a module external to such environment. Although the figures may be described with reference to other figures for ease of explanation, method 700 may be utilized with other objects and user interfaces. Additionally, while the above description states that the steps of method 700 are performed by a particular device (such as a first computing device or a second computing device), this is done for purposes of explanation only. The blocks of method 700 may be performed by one or more devices or other parts of the environment.

[0096] Aspects of the Disclosure 1. A method in a computing device for providing an experience-focused navigation session, the method including: obtaining, in one or more processors of the computing device, user data corresponding to a user of the computing device and the user's current location; determining, by the one or more processors, a semantic mapping corresponding to the user based on one or more user preferences and location history included in the user data; determining, by the one or more processors, a suggested experience-focused navigation session for the user based on the semantic mapping and the user's current location, wherein the suggested experience-focused navigation session includes an ordered list of one or more suggested points of interest; and automatically providing, by the one or more processors, the suggested experience-focused navigation session to the user as an appointment on the computing device.

[0097] 2. The method of aspect 1, further comprising generating, via the experiential learning model, proximity values ​​each corresponding to an experience-focused navigation session of the one or more experience-focused navigation sessions for the user based on the semantic mapping and the user's current location.

[0098] 3. The method of aspect 2, wherein the user data corresponding to the user includes the user's calendar data, and the method further includes generating a proximity value based on the semantic mapping, the user's current location, and the user's calendar data by an experiential learning model, and automatically providing, by one or more processors, a navigation session focused on the suggested experience to the user as an appointment on a calendar application of the computing device.

[0099] 4. The method of aspect 2 or 3, wherein the experience learning model is a machine learning model trained using the training semantic data and the training location data as input to output proximity values ​​corresponding to the plurality of experiences.

[0100] 5. The method of embodiment 4, wherein the experiential learning model is a long short-term memory (LSTM) model.

[0101] 6. The method of any of aspects 2-5, further comprising: receiving, in one or more processors, user feedback corresponding to completion of at least a portion of the navigation session focused on the suggested experience; and training, by the one or more processors, an experiential learning model using the user feedback.

[0102] 7. The method of any of aspects 1-6, wherein the suggested experience-focused navigation session includes (i) an ordered list of one or more suggested points of interest, and (ii) sequential navigational directions to each suggested point of interest on the ordered list.

[0103] 8. The method of aspect 7, wherein the suggested experience-focused navigation session includes a start time, and the method further includes receiving, by a user interface of the computing device in one or more processors, an acceptance indication from the user to confirm acceptance of the suggested experience-focused navigation session, and, upon arrival of the start time, automatically providing, by the one or more processors, continuous navigation guidance on a navigation application of the computing device to guide the user to each of the one or more suggested points of interest on the ordered list.

[0104] 9. The method of aspect 7 or 8, further comprising: receiving, in one or more processors, a quick read (QR) code scanned by a user at a first location; and, in response to receiving the QR code, determining a navigation session focused on suggested experiences, wherein the ordered list includes (i) at least a second location, and (ii) sequential navigational directions from the first location to the second location.

[0105] 10. The method of any of aspects 1-9, further comprising the step of determining, by the one or more processors, one or more indications of satisfaction corresponding to the user not completing a portion of the suggested experience-focused navigation session, wherein the one or more indications of satisfaction include (i) not visiting one or more of the one or more suggested points of interest, (ii) visiting an alternative point of interest instead of one of the one or more suggested points of interest, or (iii) receiving a rejection indication from the user of the suggested experience-focused navigation session.

[0106] 11. The method of aspect 10, further comprising combining, by one or more processors, each of the one or more indications of satisfaction with a satisfaction index value, and allocating, by the one or more processors, the satisfaction index value to the suggested experience-focused navigation session.

[0107] 12. The method of any of aspects 1-11, wherein the one or more user preferences correspond to a purchasing history of the user and the location history includes one or more locations visited by the user.

[0108] 13. The method of any of aspects 1-12, wherein the user data includes timing data including at least one of: (i) season data, (ii) day of the week data, or (iii) time of day data.

[0109] 14. The method of any of aspects 1-13, further comprising: tagging, by the one or more processors, the suggested experience-focused navigation session with one or more tags indicative of a type of experience; and uploading, by the one or more processors, the suggested experience-focused navigation session together with the one or more tags to a social media platform for sharing the suggested experience-focused navigation session with other users.

[0110] 15. A computing device for providing an experience-focused navigation session, comprising: one or more processors; and non-transitory computer-readable memory coupled to the one or more processors and storing instructions that, when executed by the one or more processors, cause the computing device to: obtain user data corresponding to a user of the computing device and the user's current location; determine a semantic mapping corresponding to the user based on one or more user preferences and a location history included in the user data; determine a suggested experience-focused navigation session for the user based on the semantic mapping and the user's current location, wherein the suggested experience-focused navigation session includes an ordered list of one or more suggested points of interest; and automatically provide the suggested experience-focused navigation session to the user as a notification on the computing device.

[0111] 16. The computing device of aspect 15, wherein the user data corresponding to the user includes the user's calendar data, and the instructions, when executed by the one or more processors, further cause the computing device to generate, via the experiential learning model, proximity values ​​corresponding to each experience-focused navigation session of the one or more experience-focused navigation sessions for the user based on the semantic mapping and the user's current location, where the proximity values ​​are based on the semantic mapping, the user's current location, and the user's calendar data, and to automatically provide, by the one or more processors, the suggested experience-focused navigation sessions to the user as appointments on a calendar application of the computing device.

[0112] 17. The computing device of aspect 15 or 16, wherein the suggested experience-focused navigation session includes (i) an ordered list of one or more suggested points of interest, (ii) sequential navigational guidance to each suggested point of interest on the ordered list, and (iii) a start time, and the instructions, when executed by the one or more processors, further cause the computing device to receive, via a user interface, an acceptance indication from a user to confirm acceptance of the suggested experience-focused navigation session, and, when the start time is reached, automatically provide sequential navigational guidance on a navigation application to guide the user to each of the one or more suggested points of interest on the ordered list.

[0113] 18. A tangible, non-transitory computer-readable medium storing instructions for providing an experience-focused navigation session, the instructions, when executed by one or more processors, causing the one or more processors to obtain user data corresponding to a user of a computing device and the user's current location, determine a semantic mapping corresponding to the user based on one or more user preferences and location history included in the user data, determine a suggested experience-focused navigation session for the user based on the semantic mapping and the user's current location, where the suggested experience-focused navigation session includes an ordered list of one or more suggested points of interest, and automatically provide the suggested experience-focused navigation session to the user as a notification on the computing device.

[0114] 19. The tangible, non-transitory computer-readable medium of aspect 18, wherein the user data corresponding to the user includes calendar data of the user, and the instructions, when executed by the one or more processors, further cause the one or more processors to generate, via an experiential learning model, a proximity value corresponding to each experience-focused navigation session of the one or more experience-focused navigation sessions for the user based on the semantic mapping and the user's current location, where the proximity value is based on the semantic mapping, the user's current location, and the user's calendar data, and to automatically provide, by the one or more processors, the suggested experience-focused navigation sessions to the user as appointments on a calendar application of the computing device.

[0115] 20. The tangible, non-transitory computer-readable medium of aspect 18 or 19, wherein the suggested experience-focused navigation session includes (i) an ordered list of one or more suggested points of interest, (ii) sequential navigational guidance to each suggested point of interest on the ordered list, and (iii) a start time, and the instructions, when executed by the one or more processors, further cause the one or more processors to receive, via a user interface, an acceptance indication from a user to confirm acceptance of the suggested experience-focused navigation session, and, when the start time is reached, automatically provide sequential navigational guidance on a navigation application to guide the user to each of the one or more suggested points of interest on the ordered list.

[0116] Various operations of the example methods described herein may be performed, at least in part, by one or more processors that are temporarily or permanently configured (e.g., by software) to perform the associated operations. Whether temporarily or permanently configured, such processors may constitute processor-implemented modules that operate to perform one or more operations or functions. Modules referred to herein may, in some example embodiments, include processor-implemented modules.

[0117] Similarly, the methods or routines described herein may be at least partially implemented by a processor. For example, at least some of the operations of the method may be performed by one or more processors or hardware modules implemented by the processors. A particular execution of an operation may be distributed among one or more processors located across several machines, as well as being present in a single machine. In some exemplary embodiments, one processor or multiple processors may be located in a single location (e.g., in a home environment, in an office environment, or as a server farm), while in other embodiments, the processors may be distributed across several locations.

[0118] The one or more processors may also operate to support execution of related operations in a "cloud computing" environment or as SaaS. For example, as indicated above, at least some of the operations may be performed by a group of computers (as examples of machines that include a processor), and these operations are accessible over a network (e.g., the Internet) and via one or more suitable interfaces (e.g., APIs).

[0119] Moreover, the figures depict several embodiments of example environments for purposes of illustration only. Those skilled in the art will readily recognize from the following discussion that alternative embodiments of the structures and methods shown herein may be employed without departing from the principles described herein.

[0120] Upon reading this disclosure, those skilled in the art will appreciate further and additional alternative structural and functional designs for providing access to a shared navigation session in accordance with the principles disclosed herein. Thus, while specific embodiments and applications have been shown and described, it should be understood that the disclosed embodiments are not limited to the precise structure and components disclosed herein. Various modifications, changes and variations that will be apparent to those skilled in the art may be made in the arrangement, operation and details of the methods and apparatus disclosed herein without departing from the spirit and scope as defined in the appended claims. [Explanation of symbols]

[0121] 100 Communication Systems 102 User Computing Devices 104 processors 106 Memory 108 Navigation Applications 110 OS 112 GPS 114 Network Module 116 User Interface 118 I / O Modules 120 Experiential Learning Model 144 Network 150 Navigation Server 152 processors 153 Memory 154 Experiential Learning Model 155 Map Database 157 Traffic Database 159 POI database 202 Calendar Application 204 GUI 206 Notification 210 GUI 212 First Appointment 302 Appointment Notice 304 Home Screen GUI 310 Experience-Focused Navigation Session Display 402 GUI 404 prompt 406a Interactive Buttons 406b Interactive buttons 412 GUI 414 Prompt 414a Interactive buttons 414b Interactive buttons 414c Interactive buttons 414d Interactive buttons 424 Prompt 424a Interactive buttons 424b Interactive buttons 424c Interactive buttons 424d Interactive buttons 504 Scannable Marks 506 User Calendar 508 Appointments 602 Scannable Marks 604 GUI 700 methods

Claims

1. 1. A method in a computing device for providing an experience-focused navigation session, comprising: obtaining, in one or more processors of the computing device, user data corresponding to a user of the computing device and a current location of the user; determining, by the one or more processors, a semantic mapping corresponding to the user based on one or more user preferences and location history included in the user data; determining, by the one or more processors, a suggested experience-focused navigation session for the user based on the semantic mapping and the current location of the user, the suggested experience-focused navigation session including an ordered list of one or more suggested points of interest; automatically providing, by the one or more processors, a navigation session focused on the suggested experience to the user as an appointment on the computing device; A method comprising:

2. 2. The method of claim 1, further comprising: generating, via an experiential learning model, proximity values ​​each corresponding to an experience-focused navigation session of one or more experience-focused navigation sessions for the user based on the semantic mapping and the current location of the user.

3. the user data corresponding to the user includes calendar data for the user; The method further comprising: generating, by the experiential learning model, the proximity value based on the semantic mapping, the current location of the user, and the calendar data of the user; automatically providing, by the one or more processors, a navigation session focused on the suggested experience to the user as the appointment on a calendar application of the computing device; 3. The method of claim 2, further comprising:

4. 3. The method of claim 2, wherein the experiential learning model is a machine learning model trained using training semantic data and training location data as inputs to output proximity values ​​corresponding to a plurality of experiences.

5. The method of claim 4 , wherein the experiential learning model is a long short-term memory (LSTM) model.

6. receiving, at the one or more processors, user feedback corresponding to completion of at least a portion of the suggested experience-focused navigation session; training, by the one or more processors, the experiential learning model with the user feedback; 3. The method of claim 2, further comprising:

7. 2. The method of claim 1 , wherein the suggested experience-focused navigation session includes (i) the ordered list of one or more suggested points of interest and (ii) sequential navigational directions to each suggested point of interest on the ordered list.

8. the suggested experience-focused navigation session includes a start time; The method further comprising: receiving, at the one or more processors via a user interface of the computing device, an acceptance indication from the user confirming acceptance of the proposed experience-focused navigation session; automatically providing, by the one or more processors, the continuous navigation guidance on a navigation application of the computing device to guide the user to each of the one or more suggested points of interest on the ordered list when the start time is reached; 8. The method of claim 7, further comprising:

9. receiving, at the one or more processors, a Quick Read (QR) code scanned by the user at a first location; determining a navigation session focused on the suggested experience in response to receiving the QR code, the ordered list including (i) at least a second location, and (ii) the continuous navigation directions from the first location to the second location; 8. The method of claim 7, further comprising:

10. 2. The method of claim 1, further comprising: determining, by the one or more processors, one or more indications of satisfaction corresponding to the user not completing a portion of the suggested experience-focused navigation session, the one or more indications of satisfaction including (i) not visiting one or more of the one or more suggested points of interest, (ii) visiting an alternative point of interest instead of one of the one or more suggested points of interest, or (iii) receiving a rejection indication from the user of the suggested experience-focused navigation session.

11. combining, by the one or more processors, each of the one or more indications of satisfaction with a satisfaction index value; assigning, by the one or more processors, the satisfaction index value to the suggested experience-focused navigation session; 11. The method of claim 10, further comprising:

12. the one or more user preferences correspond to a user's purchasing history; The method of claim 1 , wherein the location history includes one or more locations visited by the user.

13. The method of claim 1 , wherein the user data includes timing data including at least one of: (i) time of year data, (ii) day of the week data, or (iii) time of day data.

14. tagging, by the one or more processors, the suggested experience-focused navigation session with one or more tags indicating a type of experience; uploading, by the one or more processors, the suggested experience-focused navigation session along with the one or more tags to a social media platform for sharing the suggested experience-focused navigation session with other users; The method of claim 1, further comprising:

15. 1. A computing device for providing an experience-focused navigation session, comprising: one or more processors; When coupled to the one or more processors and executed by the one or more processors, the computing device obtaining user data corresponding to a user of the computing device and a current location of the user; determining a semantic mapping corresponding to the user based on one or more user preferences and location history included in the user data; determining a suggested experience-focused navigation session for the user based on the semantic mapping and the current location of the user, the suggested experience-focused navigation session including an ordered list of one or more suggested points of interest; automatically providing the suggested experience-focused navigation session to the user as a notification on the computing device. a non-transitory computer readable memory storing instructions for causing the A computing device comprising:

16. the user data corresponding to the user includes calendar data for the user; The instructions, when executed by the one or more processors, cause the computing device to: generating, by an experiential learning model, a proximity value corresponding to each experience-focused navigation session of one or more experience-focused navigation sessions for the user based on the semantic mapping and the current location of the user, the proximity value being based on the semantic mapping, the current location of the user, and the calendar data of the user; automatically providing, by the one or more processors, a navigation session focused on the suggested experience to the user as an appointment on a calendar application of the computing device. The computing device of claim 15 , further comprising:

17. the suggested experience-focused navigation session includes: (i) the ordered list of one or more suggested points of interest; (ii) sequential navigation directions to each suggested point of interest on the ordered list; and (iii) a start time; The instructions, when executed by the one or more processors, cause the computing device to: receiving, by a user interface, an acceptance indication from the user confirming acceptance of the proposed experience-focused navigation session; and automatically providing the continuous navigation guidance on a navigation application to guide the user to each of the one or more suggested points of interest on the ordered list when the start time is reached. The computing device of claim 15 , further comprising:

18. 1. A tangible, non-transitory computer readable medium having stored thereon instructions for providing an experience-focused navigation session, the instructions, when executed by one or more processors, causing the one or more processors to: obtaining user data corresponding to a user of a computing device and a current location of said user; determining a semantic mapping corresponding to the user based on one or more user preferences and location history included in the user data; determining a suggested experience-focused navigation session for the user based on the semantic mapping and the current location of the user, the suggested experience-focused navigation session including an ordered list of one or more suggested points of interest; automatically providing the suggested experience-focused navigation session to the user as a notification on the computing device. A tangible, non-transitory computer-readable medium for causing

19. the user data corresponding to the user includes calendar data for the user; The instructions, when executed by the one or more processors, cause the one or more processors to: generating, by an experiential learning model, a proximity value corresponding to each experience-focused navigation session of one or more experience-focused navigation sessions for the user based on the semantic mapping and the current location of the user, the proximity value being based on the semantic mapping, the current location of the user, and the calendar data of the user; automatically providing, by the one or more processors, a navigation session focused on the suggested experience to the user as an appointment on a calendar application of the computing device.

20. The tangible, non-transitory computer-readable medium of claim 18, further comprising:

20. the suggested experience-focused navigation session includes: (i) the ordered list of one or more suggested points of interest; (ii) sequential navigation directions to each suggested point of interest on the ordered list; and (iii) a start time; The instructions, when executed by the one or more processors, cause the one or more processors to: receiving, by a user interface, an acceptance indication from the user confirming acceptance of the proposed experience-focused navigation session; and automatically providing the continuous navigation guidance on a navigation application to guide the user to each of the one or more suggested points of interest on the ordered list when the start time is reached.

20. The tangible, non-transitory computer-readable medium of claim 18, further comprising:

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