Determine the relevance of the user's points of interest

Abstract

The present application relates to determining the relevance of a user's point of interest. Methods and apparatus relate to determining a point of interest based on content of one or more sources associated with the user. Determining a relevance score for the point of interest based on additional information associated with the user and the content. Providing point of interest information related to the point of interest based on the determined relevance score.

Description

[0001] Description of the case

[0002] This application is a divisional application of Chinese invention patent application No. 201580029652.0, filed on June 1, 2015. Technical Field

[0003] The present application relates to determining the relevance of a user's points of interest. Background Art

[0004] A user may submit a map drawing request indicating a geographic location. A map may be provided to the user in response to the request and may include one or more indications of points of interest in the geographic location. For example, a user may submit a map drawing request for a geographic area and may be provided a map including one or more businesses and / or attractions in the geographic area. Summary of the invention

[0005] The present disclosure is generally directed to technical features for determining points of interest that are private to a user. More specifically, the present disclosure is directed to methods and apparatus for determining points of interest for a user based on content from one or more electronic sources associated with the user (e.g., the user's emails, the user's calendar entries) and determining relevance scores for the points of interest based on additional information associated with the user. The additional information can be identified from the same source used to determine the points of interest and / or an alternative source can be utilized to identify the additional information. In some embodiments, points of interest and associated relevance scores are utilized in determining when and / or how to provide point of interest information for presentation to a user via a mapping application and / or other application that displays or provides one or more points of interest. For example, in some embodiments, the relevance scores of points of interest can be utilized to determine the prominence of the provided point of interest information.

[0006] The private point of interest information provided for presentation to the user results from technical features that can enable determination that the point of interest information is private to the user and can further enable the determined private point of interest information to allow the user to effectively identify that the point of interest information is private to the user. For example, the private point of interest information can be displayed more prominently to the user compared to other non-private point of interest information, thereby allowing the user to more effectively identify those points of interest that are private to the user. This presentation more prominently displays the user's private point of interest information to the user while simultaneously removing and / or demoting other private points of interest that are determined not to be private to the user, which provides technical, cognitive advantages. In some embodiments, the user's private points of interest may include those points of interest that are identified from the user's electronic sources and are considered private to the user based on a relevance score determined based on additional information associated with the user.

[0007] In some embodiments, a computer-implemented method is provided and includes the steps of identifying content from one or more electronic sources created by a user and capable of being electronically accessed by the user or electronically sent to the user; determining a point of interest based on the content, the point of interest identifying a physical location; identifying additional information associated with the user and associated with the content, wherein the identified additional information comes from a source different from one or more sources used to determine the point of interest; determining a relevance score for the point of interest based on the additional information; determining a display prominence of a visual indication of the point of interest based on the relevance score; and providing the visual indication with the determined display prominence to be presented to the user via a mapping application, the visual indication being provided so as to be presented with the display prominence at a location corresponding to the physical location on a map rendered via the mapping application.

[0008] In some embodiments, a computer-implemented method is provided and includes the steps of identifying content from one or more electronic sources associated with a user; determining a point of interest based on the content; identifying additional information associated with the user and associated with the content; determining a relevance score for the point of interest based on the additional information; and providing point of interest information related to the point of interest based on the relevance score. The point of interest information is provided for presentation to the user.

[0009] Other implementations of the method and technology described herein may each optionally include one or more of the following features.

[0010] The step of providing the point of interest information may include providing a visual indication of the point of interest via a mapping application. In some of those embodiments, the method further includes determining a display prominence of the visual indication based on the relevance score, and providing the point of interest information based on the relevance score may include providing the visual indication with the determined display prominence. In some of those embodiments, the method may further include determining whether the relevance score satisfies a threshold, and providing the point of interest information only if the relevance score satisfies the threshold.

[0011] The additional information may indicate one or more interactions of the user with the point of interest. For example, the additional information may indicate at least one of the following: the frequency of the user's interaction with the point of interest, the duration of the user's interaction with the point of interest, and the regularity of the user's interaction with the point of interest. Also, for example, the additional information may indicate the time since the user interacted with the point of interest.

[0012] The additional information may indicate a credibility metric associated with a provider of content that determines the point of interest.

[0013] The additional information may indicate prominence of content associated with the point of interest in one or more sources.

[0014] The additional information may indicate a frequency of content associated with the point of interest in one or more sources.

[0015] The step of determining the point of interest may include the steps of: determining a first location entity based on the content; determining a mapping of the first location entity to the point of interest entity based on information outside the content; and determining the point of interest based on the point of interest entity. The step of determining the point of interest may further include the steps of: determining a second location entity based on the content; and determining a mapping of the second location entity to the point of interest entity based on information outside the content. The step of determining the relevance score may include determining a first distance between the first location entity and the point of interest entity; determining a second distance between the second location entity and the point of interest entity; and determining the relevance score based on the first distance and the second distance.

[0016] The method may further include the steps of: determining a second point of interest based on the content; determining a second relevance score of the second point of interest based on the additional information; and providing second point of interest information related to the second point of interest based on the second relevance score, the second point of interest information being provided for presentation to the user.

[0017] Other embodiments may include a non-transitory computer-readable storage medium storing instructions executable by a processor to implement a method, such as one or more methods described herein. Yet another embodiment may include a system including a memory and one or more processors for executing instructions stored in the memory to implement a method, such as one or more methods described herein.

[0018] Specific embodiments of the subject matter described herein determine points of interest based on content from sources associated with a user. Additional information from one or more sources may be utilized to determine a relevance score for the determined points of interest. Specific embodiments determine when and / or how to provide point of interest information to a user based on the determined relevance score for the point of interest.

[0019] It should be appreciated that all combinations of the above concepts and additional concepts described in greater detail herein are considered part of the subject matter disclosed herein. For example, all combinations of claimed subject matter appearing at the end of this disclosure are considered part of the subject matter disclosed herein. BRIEF DESCRIPTION OF THE DRAWINGS

[0020] Figure 1is a block diagram of an exemplary environment in which points of interest of a user may be determined and / or provided to the user.

[0021] Figure 2 is an example of a sample message including content that may be used to determine a point of interest.

[0022] Figure 3 is an example of another sample message including content that may be used to determine a point of interest.

[0023] Figure 4 is an example of a sample message including content that may be used as additional information for determining a relevance score for a point of interest.

[0024] Figure 5A is an example graphical user interface for providing a map including indications of points of interest to a user.

[0025] Figure 5B is an exemplary graphical user interface for providing a map with points of interest to a user based on relevance scores determined for the points of interest.

[0026] Figure 5C is another exemplary graphical user interface for providing a map with points of interest to a user based on relevance scores determined for the points of interest.

[0027] Figure 6 is an example graph of identified points of interest and additional locations.

[0028] Figure 7 is a flow chart illustrating an example method of determining points of interest of a user based on content of one or more sources associated with the user.

[0029] Figure 8 A block diagram of an example computer system is shown. DETAILED DESCRIPTION

[0030] One or more points of interest of a user can be determined from the content of an electronic source associated with the user. Additional information can also be identified from the content of one or more electronic sources associated with the user and used to determine a relevance score for the determined points of interest. For example, a user can be associated with an email including flight information such as the arrival airport of a flight and / or the departure airport of an incoming flight. At the same time, for example, the email is associated with one or more times that can be used to determine the relevance score of the point of interest, such as the time when the user receives the email and / or the time when the user last accessed the email. The content of the email can be used to determine the arrival and / or departure airport as a point of interest. Additional information can be identified from the content of the email, such as the sender of the email and / or the prominence of the airport indication in the email. At the same time, for example, additional information can be identified from one or more additional sources associated with the user, such as the user's calendar entry and / or the user's location information.

[0031] Based on the identified additional information associated with the user, a relevance score for the point of interest is determined. The relevance score indicates the likelihood that the point of interest is relevant to the user and / or that the user is interested in being provided with information related to the point of interest. For example, a relevance score for an arrival airport that can be determined as a point of interest can be determined based on identifying an email including content about the airport sent from a trusted source such as an airline reservation department and / or from an online travel booking agent. At the same time, for example, a relevance score for the arrival airport point of interest can be determined based on identifying that the user has created a schedule entry for a flight including the same airport code as the determined arrival airport point of interest. At the same time, for example, the user's previous location information can be utilized and the relevance score for the arrival airport point of interest can be determined based on identifying the frequency with which the user appears at the arrival airport. For example, in some embodiments, the relevance score of the arrival airport point of interest that the user visits more often can be determined to indicate a lower relevance compared to the relevance score of another point of interest that the user visits less often. Such a relevance score can reflect that the airport that the user visits more often is more familiar to the user and the user is less interested. At the same time, for example, in some instances, a relevance score for a first point of interest that indicates more relevance than the relevance score of a second point of interest can be determined, and the user visits the second point of interest less often relative to the first point of interest.

[0032] One or more points of interest may be provided to a user via one or more applications such as a mapping application. In some embodiments, one or more determined points of interest are provided based on a relevance score of the determined points of interest. In some embodiments, the prominence of the provided point of interest information for the point of interest may be determined based on the relevance score of the point of interest. For example, the relevance score of the point of interest may be utilized to determine the size of an indication of the point of interest on a map and / or the ranking of the point of interest in a list of points of interest. In some embodiments, it may be determined when to provide the point of interest information for the point of interest to the user based on the relevance score of the point of interest. For example, a point of interest may be provided to the user only if the relevance score meets a threshold.

[0033] Figure 1 The figure illustrates a block diagram of an example environment in which a user's points of interest may be determined and / or provided to the user. The example environment includes a communication network 101 that facilitates communication between various components in the environment. In some embodiments, the communication network 101 may include the Internet, one or more intranets, and / or one or more bus subsystems. The communication network 101 may optionally utilize one or more standard communication technologies, protocols, and / or inter-process communication technologies. The example environment also includes a point of interest engine 105, a content database 110, a relevance engine 115, an entity database 120, and a user device 125. The user device 125 may execute one or more applications, such as a web browser and / or a mapping application.

[0034] In some embodiments, the point of interest engine 105 can identify an electronic source associated with a user. The electronic source can include, for example, email, instant messaging, documents, Web history, calendar entries, the user's current location data, the user's previous location data, the address of the contact from the user's contact set (e.g., email contact, telephone contact), etc. In the case where the system described herein collects personal information about the user, or can utilize personal information, it can provide the user with an opportunity to control whether the program or functional component collects user information (e.g., information about the user's social network, social actions or activities, occupations, user preferences, or the user's current geographic location) or control whether and / or how to receive content from a content server that may be more relevant to the user. At the same time, some data can be processed in one or more ways before being stored or used, so that personal identifiable information is removed. For example, the user's identity can be processed so that personal identifiable information about the user cannot be determined, or the user's geographic location (e.g., to the city, zip code, or state level) of the user who obtains geographic location information can be summarized so that the user's geographic specific location cannot be determined. Thus, the user has the right to control how to collect and / or use information about the user. In some implementations, the points of interest engine 105 can identify sources that have certain data that has been processed in one or more ways to remove personally identifying information and / or other information.

[0035] The points of interest engine 105 can identify content from one or more sources and determine whether the identified content is associated with a point of interest. The content from the source can include, for example, one or more terms from the source, the format of one or more terms from the source, the location of one or more terms in the source, the author and / or sender of the source, and / or metadata that can be included in the source. In some embodiments, the points of interest engine 105 can identify the entire content of the source. For example, the points of interest engine 105 can identify the entire content of a user's email. In some embodiments, the points of interest engine 105 can identify only portions of content from the source that are potentially relevant to a point of interest.

[0036] In some embodiments, the content database 110 may include one or more storage media and one or more aspects that can be used to store and / or access the information described herein. For example, the content database 110 may be used by one or more components to store, modify, and / or access content associated with a user from one or more sources. In some embodiments, the content database 110 may store content and / or sources for multiple users, and, for each entry, only the user and / or one or more other users or components (such as the point of interest engine 105) authorized by the user may be allowed to access the source and / or content. In some other embodiments, the content database 110 may only store content and / or sources for a single user.

[0037] In this specification, the term "database" is used broadly to refer to any data set. The data in the database need not be structured in any particular way, or may be completely unstructured, and can be stored on a storage device in one or more locations. Thus, for example, a database may include multiple data sets, each of which may be organized and accessed differently. At the same time, in this specification, the term "entry" will be used broadly to refer to any mapping of multiple related information items. A single entry need not appear in a single storage device, and may include pointers or other indications of information items that may appear on other storage devices. For example, an entry may include multiple nodes that are mapped to each other, each node including an identifier of an entity or other information item that may appear in another data structure and / or another storage medium.

[0038] In some implementations, the points of interest engine 105 may identify content associated with the user via the content database 110. For example, the content database 110 may include content from one or more sources that have been previously identified as potentially including content related to one or more points of interest. At the same time, for example, the content database 110 may include content from one or more sources that have not been previously identified by the points of interest engine 105 or other components as including content related to points of interest.

[0039] In some embodiments, the points of interest engine 105 can identify all of the user's content from the content database 110. In some embodiments, the points of interest engine 105 can use rule-based and / or other methods to identify a subset of sources and / or content that may be related to points of interest. For example, the points of interest engine 105 can determine that all sources that include addresses may include content related to points of interest. At the same time, for example, the points of interest engine 105 can determine that all content originating from airlines may be associated with points of interest. At the same time, for example, the points of interest engine 105 can determine that sources that include one or more key terms are likely to be related to points of interest, such as sources that include "flight", "hotel", and / or "reservations".

[0040] The point of interest engine 105 can determine points of interest based on the identified content. Points of interest are identifiers of physical locations that can be used to present information related to the physical location to the user. Examples of points of interest include unique identifiers of physical locations, such as one or more street addresses of the location, entity identifiers of the location, and / or one or more longitude and latitude coordinates, etc. At the same time, points of interest can define physical locations with arbitrary levels of granularity. For example, a point of interest can define specific coordinates, a specific building, a specific part of a building, a specific geographic area (a neighborhood, a park, an entire city), and / or a portion of a specific terrain feature (a street, a highway, a body of water, a bridge, etc.).

[0041] In some embodiments, the points of interest engine 105 may utilize one or more rules to determine points of interest from the identified content. For example, the points of interest engine 105 may determine points of interest based on identifying one or more terms that conform to an address (e.g., "123 Airport Road" conforming to the rule [number] [street name]). Also, for example, the points of interest engine 105 may identify an airport code based on identifying three capital letters (e.g., "LAX" and / or "SFO") near one or more terms indicating an airport (such as "airport", "departs", and / or "arrives").

[0042] refer to Figure 2 , provides an example of a sample source including content that can be used to determine points of interest. The source is an email 200 that can be provided to a user in response to the user booking a flight via an airline and / or an online travel company. The email includes departure information including airport name 210 and arrival information. In addition, email 200 includes sender information 205.

[0043] The points of interest engine 105 may receive the email 200 via the content database 110 and / or the email service. In some implementations, the points of interest engine 105 may utilize a rule-based approach to determine the points of interest based on one or more terms in the email 200. For example, the points of interest engine 105 may identify the airport name 210 "LAX" as meeting one or more rules for identifying an airport code, and use "LAX" as a point of interest and / or determine the point of interest based on "LAX" (e.g., an address mapped to LAX, a latitude / longitude mapped to LAX, and / or an entity identifier mapped to LAX). In some implementations, the points of interest engine 105 may utilize a rule-based approach to determine additional information associated with the determined points of interest. For example, the points of interest engine 105 may identify "April 30, 2014" as satisfying one or more rules for identifying dates, and further identify "April 30, 2014" as being associated with LAX based on one or more rules (such as considering the proximity of "April 30, 2014" to "LAX").

[0044] In some embodiments, the interest point engine 105 can determine the interest point based on one or more terms in the email 200 using a classifier-based approach. For example, the interest point engine 105 can include a classifier that is trained to identify whether one or more segments of a source indicate an interest point based on one or more segments of the source and / or additional signals. For example, the interest point engine 105 can classify a term in an email as indicating an interest point based on one or more signals from the content of the email, such as a signal related to the term itself, a signal related to one or more terms before and after the term, a signal related to the position of the term in the email, and / or a signal related to the metadata of the source. One or more signals can optionally include a signal based on processing the source by one or more additional components. For example, the signal can include a signal related to the part of speech of one or more terms, a grammatical relationship of one or more terms, etc., and these signals can be based on the output of the parser. The classifier of the interest point engine 105 can be trained to divide segments into interest points based on previous training using supervised or semi-supervised training techniques. Additional or alternative rule-based and / or classifier-based techniques can be used to determine the interest point from the content of the source.

[0045] In some implementations, the points of interest engine 105 may determine points of interest directly based on content from a source. Figure 3 , provides another example source including content that can be used to determine points of interest. The source is an email 300 that includes sender information 305, a rental car location address 310, and a hotel address 315. The points of interest engine 105 can determine "123 Airport Road" and / or "200 S. Main Street" as points of interest based on terms that conform to the address format. At the same time, for example, the points of interest engine 105 can determine that "123 Airport Road" is a point of interest using other terms other than "123 Airport Road", such as by identifying that "123 Airport Road" is near the hotel address 315, determining that the sender of the email 300 is related to the rental car location, and / or based on other terms in the email 300.

[0046] In some implementations, the point of interest engine 105 may indirectly determine the point of interest based on one or more terms of the identified content. Figure 2, the email 200 includes the airport name 210 "LAX" as content. The points of interest engine 105 can identify "LAX" as an airport code based on, for example, one or more additional terms in the message ("Flight", "Departs", "Arrives", etc.) and / or comparison with a list of airport codes. The points of interest engine 105 can utilize the entity database 120 to identify an entity mapped to "LAX" and further identify an address mapped to the same entity, such as "500Airport Road". The points of interest engine 105 can determine the relevant address as a point of interest based on the association between the identified airport name 210 and the address "500Airport Road" in the entity database 120.

[0047] In some implementations, the points of interest engine 105 can identify a location from the content of a source and determine a point of interest associated with the identified location. Figure 3 , the points of interest engine 105 may identify "123Airport Road" as an address and further identify "123AirportRoad" as the address of a car rental location based on, for example, one or more terms in the email 300 and / or based on identifying a "car rentallocation" entity mapped to "123Airport Road" in the entity database 120. The points of interest engine 105 may determine a gas station near the car rental location as a point of interest related to the car rental location. The points of interest engine 105 may determine a point of interest as a gas station near the car rental location. For example, the points of interest engine 105 may identify "123Airport Road" as content in the email 300, identify a "rental car location" entity mapped to "123Airport Road", and further identify a "gas station" associated with the "rental car location" entity. The points of interest engine 105 may determine the address or other identifier of the "gas station" entity as a point of interest based on the identified association.

[0048] In some embodiments, the points of interest engine 105 can identify two or more locations from the content of the source and determine points of interest that include a path between the two or more locations. For example, the points of interest engine 105 can identify a hotel location and an airport location from one or more sources. The points of interest engine 105 can determine points of interest that are paths between the identified locations. For example, the points of interest engine 105 can identify one or more roads, bus routes, and / or other paths that can be used by a user to travel from one of the identified locations to one or more other locations.

[0049] In some embodiments, the points of interest engine 105 may determine points of interest from related locations identified from the content based on the determined relationship between the category of the identified location and the category associated with the point of interest. The relationship between the location identified in the content of the source and the point of interest may be determined from the entity database 120. For example, the point of interest engine 105 may determine that "123 Airport Road" is a location with an entity category "rental car location" and determine from one or more databases (such as the entity database 120) that the entity category "rental car location" and the entity category "gasstation" are associated with each other. In some embodiments, the point of interest engine 105 may identify a gas station close to the rental car location based on identifying the relationship between "rental carlocation" and "gas station". In some embodiments, a rule may be used to determine the relationship between the location identified from the content of the source and the point of interest. For example, the point of interest engine 105 may identify a rental car location in the content of the source and determine a gas station as a point of interest based on identifying a rental car location identification rule.

[0050] In some implementations, the POI engine 105 may determine multiple POIs based on the same segment of the source content. Figure 4 , providing an example diagram of sources that can be used to determine multiple points of interest. The message thread includes a reference to "ChainRestaurant", which can have multiple locations. The points of interest engine 105 can determine multiple locations of "Chain Restaurant" from one or more databases and determine that each location can be a point of interest for the user. For example, the points of interest engine 105 can identify a "Chain Restaurant" entity in the entity database 120 that is mapped to multiple addresses. In some embodiments, multiple points of interest can be provided to the relevance engine 115 to determine whether one or more of the locations are more relevant to the user based on additional information from one or more sources, as described herein. For example, the points of interest engine 105 can determine multiple gas stations as points of interest and the relevance engine 115 can determine the relevance score of the point of interest based on the distance between the gas station and one or more locations, such as the distance between each gas station and a rental car location.

[0051] The point of interest engine 105 may store one or more determined points of interest in the content database 110 for later use by one or more components. For example, the point of interest engine 105 may store "123 Airport Road" as a location in the content database 110 and later provide "123 Airport Road" to the relevance engine 115 to determine the relevance score of the point of interest. In some embodiments, the point of interest engine 105 may store all or part of the content used to determine the point of interest together with the point of interest in the content database 110. For example, the point of interest engine 105 may determine the point of interest "123 Airport Road" from the email 300 and store the email 300 together with the determined point of interest in the content database 110. At the same time, for example, the point of interest engine 105 may only store "123 Airport Road" together with the sender information 305.

[0052] The relevance engine 115 identifies additional information from one or more sources associated with the user and uses the additional information to determine the relevance score of the point of interest based on the additional information. In some embodiments, the relevance engine 115 can be a component of the point of interest engine 105. For example, the point of interest engine 105 can identify content, determine a point of interest from the content, and determine the relevance score of the point of interest based on the additional information. In some embodiments, the relevance engine 115 identifies additional information used to determine the point of interest from the content of the same source. For example, the point of interest engine 105 can determine the point of interest based on the user's email, and the relevance engine 115 can determine the relevance score based on additional information included in the email, such as the sender of the email, the format of one or more terms in the email, and / or the reference location of the point of interest in the email. In some embodiments, the content of the source may not include identifying information. For example, the relevance engine 115 can be provided with a classification of the sender of the message (a user's private contact, an advertiser, an online service, etc.) without providing identification information of the sender. In some embodiments, the relevance engine 115 can identify additional information from one or more sources separate from the source used by the point of interest engine 105 to determine the point of interest. For example, points of interest engine 105 may determine points of interest from a user's email, while relevance engine 115 may identify a second email as additional information and / or identify additional information from different types of sources, such as the user's GPS data and / or the user's Web history.

[0053] In some embodiments, the relevance engine 115 may identify additional information from one or more sources previously used to determine the point of interest. For example, the point of interest engine 105 may determine the point of interest from email 1 and provide the point of interest to the relevance engine 115 to determine an initial relevance score for the point of interest. The relevance engine 115 may store the point of interest, the determined relevance score, and / or the content from the source in the content database 110. Next, the point of interest engine 105 may determine the same point of interest from email 2 and provide the point of interest to the relevance engine 115. The relevance engine 115 may identify email 1 as additional information to determine the relevance score for the point of interest. For example, the relevance engine 115 may identify the number of occurrences of references to the point of interest in email 1 as additional information to determine the relevance score. At the same time, for example, the relevance engine 115 may determine a new relevance score using the previously determined relevance score for the point of interest. The relevance engine 115 may store the point of interest, the new relevance score, and / or the content of email 1 and / or email 2 in the content database 110 for subsequent determination of the relevance score.

[0054] The relevance engine 115 may identify additional information from a source based on identifying one or more sources that include content related to the determined point of interest. For example, the point of interest engine 105 may provide the point of interest to the relevance engine 115 and the relevance engine 115 may identify the content that includes the point of interest. For example, the point of interest engine 105 may determine "123 Airport Road" as a point of interest based on the email 300, and store the point of interest and the content of the email 300 in the content database 110. Subsequently, the point of interest engine 105 may determine "123 Airport Road" from another source and provide the relevance engine 115 with "123 Airport Road" as a point of interest. The relevance engine 115 may identify the email 300 as additional information from the content database 110 based on identifying that the email 300 was previously determined to include content associated with "123 Airport Road". In some embodiments, the point of interest engine 105 may determine the point of interest as an entity identifier. For example, the point of interest engine 105 may determine the point of interest as the "Los Angeles International Airport" entity. The relevance engine 115 may identify additional information in sources that include content mapped to the point of interest entity, such as sources that include an alias for the entity (eg, "LAX") and / or other attributes of the entity (eg, the address of an airport).

[0055] In some implementations, the additional information may include the prominence of content associated with the determined point of interest in one or more sources. For example, the point of interest engine 105 may provide the point of interest "Chain Restaurant" to the relevance engine 115 based on the content of the email 400. The relevance engine 115 may identify the term "Chain Restaurant" in the title 415 of the email 400 as additional information that may be used to determine the relevance score for "Chain Restaurant". At the same time, for example, the relevance engine 115 may identify the special format of the reference to the point of interest in the content of one or more sources as additional information that may be used to determine the relevance score of the point of interest.

[0056] In some implementations, the additional information may include information about the sender and / or author of the content source containing the determined point of interest. For example, the point of interest engine 105 may provide the determined point of interest "LAX" and "booking@exampleairline.com" as the sender of the email 200 to the relevance engine 115. Alternatively, the point of interest engine 105 may provide all or part of the email 200 to the relevance engine 115 and the relevance engine 115 may identify the sender of the email 200. At the same time, for example, the point of interest engine 105 may determine the point of interest from the user's calendar entry and provide the point of interest to the relevance engine 115 along with an indication that the user is the creator of the content.

[0057] In some embodiments, the relevance engine 115 may identify additional information including the user's location information. For example, the relevance engine 115 may identify the user's previous location as indicated by GPS, triangulation of cellular phone signals, user check-in registration, etc. Also, for example, the relevance engine 115 may identify the user's online check-in registration at one or more locations. In some embodiments, the user's previous location information may be identified from the content database 110. In some embodiments, the point of interest engine 105 may provide the relevance engine 115 with points of interest and additional information including location information, which may be used by the relevance engine 115 to determine a relevance score.

[0058] For example, refer to Figure 4, the point of interest engine 105 may determine multiple points of interest for “ChainRestaurant” based on the content of the email 400. The point of interest engine 105 may provide the relevance engine 115 with the address of the point of interest “ChainRestaurant” and / or one or more locations of “Chain Restaurant”. In some embodiments, the relevance engine 115 may identify indications of one or more instances of users located at and / or near one or more of the determined locations of “Chain Restaurant”. The relevance engine 115 may utilize the identified occurrence instances of users at and / or near the locations of “Chain Restaurant” to determine a relevance score for one or more determined points of interest.

[0059] The relevance engine 115 may determine a relevance score for the determined point of interest based on the identified additional information. In some embodiments, the relevance engine 115 may determine the relevance score as a binary value. For example, the relevance engine 115 may determine that the point of interest is of interest to the user or is not of interest to the user. In some embodiments, the relevance engine 115 may determine the relevance score as a numerical value, such as a value from 0 to 1 or a value from 0 to 100. For example, the relevance engine 115 may determine the relevance score for the point of interest, wherein a value of 0 indicates that the user is not interested in providing the point of interest, and 100 indicates that the user is very interested in the point of interest (values ​​in between indicate relative interest).

[0060] In some embodiments, the relevance score may be determined based on references to the identified point of interest in the content of one or more sources associated with the user. In some embodiments, the relevance score of the point of interest may be based on a count of sources associated with the user that include references to the point of interest. For example, the point of interest engine 105 may determine the point of interest and provide the point of interest to the relevance engine 115. In some embodiments, the relevance engine 115 may identify the source that includes the reference to the point of interest and determine the relevance score based on the count of the source that includes at least one reference to the point of interest. For example, the relevance engine 115 may determine the relevance score based on determining that a threshold number of sources include references to the point of interest and / or a count of sources that include references to the point of interest during a time period. At the same time, for example, the relevance engine 115 may determine the relevance score based on determining the frequency of sources that include references to the point of interest (the frequency of sources that include references within a time period among all sources associated with the user, among sources that include the point of interest, etc.). In some embodiments, the relevance score of the point of interest may be based on a count of references to the determined point of interest in the content of one or more sources. For example, the points of interest engine 105 may provide the relevance engine 115 with the determined points of interest and the content from the source used to determine the points of interest. The relevance engine 115 may identify a reference count to the point of interest in the source and / or the relevance engine 115 may identify other sources that include references to the point of interest and determine the frequency of the number of references to the point of interest in multiple sources. The relevance engine 115 may utilize the reference count to the point of interest to determine a relevance score for the point of interest. At the same time, for example, the relevance engine 115 may determine the frequency of references to the point of interest. For example, the relevance engine 115 may determine the relevance score based on the frequency of references to the point of interest in all references to the point of interest, the frequency of references to the point of interest in all references to the point of interest in the source, the frequency of references over a period of time, etc.

[0061] In some embodiments, the relevance score may be based on the time associated with one or more sources that include content related to the point of interest. In some embodiments, the relevance score may be based on the recency of the reference to the point of interest determined in one or more sources. For example, the relevance engine 115 may determine that the relevance score of the point of interest mentioned in the source 24 hours ago indicates that the user is more interested in the point of interest than the point of interest mentioned in the source in the past week. At the same time, for example, the relevance engine 115 may determine the relevance score of the point of interest based on the time of the reference in one or more sources that include the reference to the point of interest. For example, based on the fact that the reference in the source that includes a more recent time may be more relevant to the user than the point of interest mentioned at an earlier time, the relevance engine 115 may determine a relevance score indicating more relevance for the point of interest referenced in the source including "We ate there last week (We went to eat last week)" compared to the point of interest referenced in the source including "We ate there last year (We went to eat last year)".

[0062] In some embodiments, the relevance score of the point of interest can be based on an indication of the regularity of the user's interaction with the point of interest. For example, the relevance score can be based on identifying that the user interacts with the point of interest on a regular basis, such as on a monthly basis, at least one morning per week, and / or at least once per week, month, year, etc. The indication of the regularity of the interaction with the point of interest can be determined based on, for example, location information indicating that the user is at and / or near the point of interest multiple times over a period of time, recurring calendar events of the user related to the point of interest, multiple views of one or more documents associated with the point of interest over a period of time, multiple search queries of the user related to the point of interest over a period of time, etc.

[0063] In some embodiments, one or more additional times associated with a source can be used to determine a relevance score for a point of interest related to the content of the source. For example, a message may include content related to a point of interest. A message may be associated with a reception time indicating when the user received the message and / or a viewing time indicating when the user accessed the message. For example, the relevance engine 115 may determine a relevance score when the user first receives the message that indicates greater relevance than a later time after the reception time. At the same time, for example, the relevance engine 115 may determine a relevance score for a first time shortly after the user first accesses the message that indicates greater relevance than a relevance score determined at a later time after the first time.

[0064] In some implementations, the relevance score of a point of interest may be determined based on the current time associated with the content related to the point of interest. Figure 3, the hotel address 315 may be the determined point of interest. In some implementations, the relevance engine 115 may identify the check-in date and the check-out date as additional information to determine the relevance score of the point of interest. The relevance engine 115 may determine the relevance score of the point of interest indicating a more relevant correlation between the check-in date and the check-out date compared to the determined relevance score of the point of interest after the check-out date. Also, for example, the relevance engine 115 may determine a relevance score indicating a more relevant correlation to the point of interest as the check-in time approaches, reaching a peak relevance score on the check-in date, and decreasing after the check-out date.

[0065] In some embodiments, the relevance score may be determined based on additional information including location information for the user. In some embodiments, the relevance score for the point of interest may be based on the frequency of users near the point of interest. For example, the relevance score may be based on the number of times the user has visited the point of interest, the frequency of the user's visits to the first point of interest and the second determined point of interest, the recency of the user's visits to the point of interest, and / or the length of time the user has visited the point of interest in the past. For example, based on the content of the email 400, such as by identifying two addresses mapped to entities associated with "Chain Restaurant" in the entity database 120, the point of interest engine 105 may determine that "Chain Restaurant" is a point of interest and that "Chain Restaurant" has two locations. The point of interest engine 105 may provide the two addresses to the relevance engine 115 and the relevance engine 115 may determine the relevance score of each location in the location based on the user's appearance identified at each location in the location. The relevance score of each location in the location may be determined using the count of the user being at each location in the location (or the frequency of the user being at one location in the location compared to another location), the recency of the user being at each location in the location, and / or the length of the user's stay at each location in the location.

[0066] In some implementations, a relevance score may be determined based on identifying a distance between one or more determined points of interest and another location identified from one or more sources of the user. For example, as previously described, the points of interest engine 105 may determine multiple gas station locations as points of interest based on the content of the email 300. The relevance engine 115 may identify the email 300 as additional information and further identify both "123 Airport Road" and "200 S. Main Street" as locations included in the content of the email 300. The relevance engine 115 may determine a relevance score for a given gas station of a determined point of interest (i.e., gas station location) based on determining a distance between the given gas station and one or both of the identified addresses.

[0067] In some embodiments, a user may be provided with a personal map having one or more characteristics determined based on the relevance scores of the points of interest. The personal map may have one or more different visual indications that may be adjusted based on the relevance scores. For example, a user may be provided with a personal map having one or more points of interest that are displayed with varying illustrations (e.g., special symbols based on the type of point of interest), various colors, various sizes, and / or in various layouts (e.g., fonts, bold, italics). At the same time, for example, additional information about the points of interest may be provided via a customized point of interest display, such as an airport point of interest provided with an identified flight boarding time and / or flight number that has been identified from content from one or more sources related to the point of interest.

[0068] For example, refer to Figure 6 , provides an example illustration of determined points of interest and additional locations. The illustration includes two gas stations, "Gas Station 1" and "Gas Station 2," which can be determined as points of interest by the points of interest engine 105 using the content of the email 300, as described herein. The relevance engine 115 can identify the rental car address 310 and the hotel address 315 as additional information, as described herein. Figure 8 , providing hotel locations and car rental locations. In some embodiments, the relevance engine 115 can determine the relevance scores of "Gas Station 1" and "Gas Station 2" based on the distance between the point of interest and the identified car rental address 310 and hotel address 315. For example, the relevance score of "GasStation 1" can be determined based on the distance between "Gas Station 1" and the hotel address 315 and / or the distance between "Gas Station 1" and the car rental address 310. At the same time, for example, the relevance engine 115 can determine the relevance score of "Gas Station 2" based on the distance between "Gas Station 2" and the hotel address 315 and / or the distance between "Gas Station 2" and the car rental address 310.

[0069] In some embodiments, when used to determine the relevance score, the distance between the point of interest and the additionally identified location can be weighted. For example, the relevance engine 115 can determine that the distance between the determined gas station point of interest and the identified rental car location can be weighted greater than the distance between the gas station point of interest and the identified hotel location. The relevance engine 115 can determine the weights assigned to the one or more distances between the additionally identified location and the determined point of interest based on, for example, the identified trends of previous location data, the weights associated with one or more entities, and / or the relationships between entities in the entity database 120, and / or one or more factors identified from the content of the source (prominence of the additionally identified location in the content, the format of the content, metadata, etc.). Based on determining that "Gas Station 2" is closer to "Rental CarLocation", a relevance score of "GasStation 2" indicating that it is more relevant to the user can be determined compared to the relevance score of "Gas Station 1". In some embodiments, when determining the relevance score, the distances between the determined points of interest and the additional locations can be weighted evenly. In some embodiments, the relevance score can be determined using possible paths between the additionally identified locations. For example, a relevance score for one or more of the gas station points of interest may be determined based on a deviation distance from a path between "Hotel" and "Rental CarLocation."

[0070] In some implementations, the relevance score may be based on the credibility of the source of the source of the additional information. For example, the relevance engine 115 may determine a relevance score indicating that points of interest determined from a calendar entry created by a user are more relevant than points of interest determined from an email from an unsolicited advertiser.

[0071] The relevance scores may be utilized to provide indications of points of interest on a map responsive to a map drawing request. For example, in some implementations, a user may submit a map drawing request for a geographic area. A map responsive to the map drawing request may be provided to the user via user device 125. In some implementations, a map including indications of one or more points of interest contained in the geographic area may be provided to the user. For example, a map including restaurants, hotels, tourist attractions, and / or other points of interest provided on the map may be provided to the user via a graphical indication.

[0072] In some embodiments, the one or more points of interest provided as points of interest may be points of interest provided by the points of interest engine 105. For example, the points of interest engine 105 may determine the points of interest based on content in a source associated with the user, and may provide an indication such as a star, an information box, and / or another indication of the location of the point of interest to the user on a map in response to the map drawing request, wherein the mapped geographic area includes the point of interest. In some embodiments, the determined points of interest may be provided to the user in addition to other points of interest not determined by the points of interest engine 105. In some embodiments, the indications of the points of interest determined by the points of interest engine 105 may have different indications than other points of interest not determined by the points of interest engine 105. For example, the points of interest determined by the points of interest engine 105 are provided in a color that is different from one or more colors used for other indications of the points of interest.

[0073] refer to Figure 5A , an exemplary graphical user interface for providing a user with indications including points of interest is given. Map 500A includes indications of two points of interest, restaurant indication 505A and restaurant indication 510A. In some embodiments, one or both of restaurant indications 505A and 510A can be determined by point of interest engine 105. For example, point of interest engine 105 can determine points of interest corresponding to restaurant indications 505A and 510A based on content from email 400.

[0074] In some embodiments, based on the determined relevance score of the point of interest, Figure 1 For example, only when the determined relevance score satisfies a threshold value, the location is associated with the location. Figure 1 In some embodiments, prominence is provided to a point of interest based on a relevance score of the point of interest. For example, if a first point of interest has a relevance score indicating that it is more relevant than a second point of interest, then the point of interest may be provided with a higher prominence than the second point of interest. Prominence may include, for example, a font size of the point of interest indication, a color of the point of interest indication, and / or a size of a marker of the point of interest indication.

[0075] For example, refer to Figure 5B , providing a relevance score based on the determination of the point of interest, and providing a user with an example graphical user interface of a map with points of interest. Map 500B can be used to Figure 5A Map 500B includes restaurant indication 505B. Restaurant indication 505B may be the same indication as restaurant indication 505A. In some embodiments, the restaurant indication 505B may be associated with a map 500B based on a determined relevance score of a corresponding point of interest that satisfies a threshold. Figure 1The restaurant indication 505B is provided together with the map 500A. The additional point of interest indications of the restaurant indication 510A of the map 500A are not provided together with the map 500B. In some embodiments, the point of interest engine 105 can determine a point of interest corresponding to the restaurant of the restaurant indication 510A and the relevance engine 115 can determine a relevance score for the point of interest. Based on determining that the relevance score of the point of interest does not meet the threshold value, such as Figure 5B As illustrated, an indication of a restaurant corresponding to restaurant indication 510A may not be provided.

[0076] refer to Figure 5C , an exemplary graphical user interface for providing a user with a map having points of interest having prominence based on a determined relevance score for the points of interest is given. Map 500C may be used to identify a user who has a map having points of interest. Figure 5A Maps of 500A and Figure 5B In some embodiments, the points of interest engine 105 may determine points of interest corresponding to restaurant indication 505C and restaurant indication 510C. In some embodiments, the relevance engine 115 may determine a relevance score for the points of interest, as described herein. For example, the points of interest engine 105 may determine a relevance score for the points of interest based on the restaurant indication 505C and the restaurant indication 510C. Figure 4 The relevance engine 115 may determine the relevance score of the point of interest based on the content of the email 400 and / or from additional sources, such as the user's previous location history, the number of indications of each of the points of interest in the additional sources, and / or content from one or more additional sources. Based on the relevance score of the point of interest corresponding to each indication in the indication, the restaurant indication 505C is provided with a higher prominence than the restaurant indication 510C. For example, the relevance engine 115 may determine the relevance score of the restaurant indicated by the restaurant indication 505C, which indicates a more relevant restaurant, compared to the determined relevance score of the point of interest represented by the restaurant indication 510C. For example, based on the user's previous location information and / or the additional content including one or more of the points of interest, the relevance engine 115 may determine that the user may be more interested in the point of interest corresponding to the restaurant indication 505C than the point of interest represented by the restaurant indication 510C. In the illustrated interface, the restaurant indication 510C has a larger font than the restaurant indication 510C. In addition, the restaurant indication 505C is provided in bold. In some embodiments, additional or alternative prominent indications may be utilized, such as different colors and / or different markings.

[0077] In some embodiments, the relevance scores of the points of interest may be utilized to provide a user with a list of points of interest, wherein the order of the points of interest is determined based on the relevance scores. For example, a list of nearby points of interest may be provided to the user via an application executed on the user device 125. Points of interest having relevance scores indicating more relevance may be provided higher in the list than points of interest having relevance scores indicating less relevance. At the same time, for example, a point of interest is provided in the list only if the relevance score satisfies a threshold value.

[0078] refer to Figure 7 , illustrates a flow chart of an example method for determining a user's points of interest based on the content of one or more sources associated with the user. Other implementations may perform steps in a different order, omit certain steps, and / or perform steps that are different from the steps in the example method. Figure 7 For convenience, reference will be made to the method that can be performed. Figure 1 One or more components (such as the point of interest engine 105) are described Figure 7 aspects.

[0079] At step 700, content is identified from one or more sources. In some implementations, the content is identified by a component that shares one or more characteristics with the points of interest engine 105. In some implementations, sources that may include content associated with a point of interest may be identified by a component that shares one or more characteristics with the points of interest engine 105. For example, the points of interest engine 105 may identify emails, instant messages, web history, the user's previous location information, calendar entries, and / or other documents associated with the user as sources that may include content related to a point of interest.

[0080] In step 705, points of interest are determined based on the content of the identified source. In some embodiments, points of interest may be determined based on indications of points of interest in the source. For example, "123Airport Road" may be determined as a point of interest based on identifying the term "123AirportRoad" in the content of the source. In some embodiments, points of interest related to the location indicated in the message may be determined. For example, an email may include information related to renting a car and the points of interest engine 105 may determine one or more gas stations as points of interest. The points of interest engine 105 may determine one or more points of interest related to the location in the content based on, for example, identifying a relationship between an entity indicated in the content and a related entity identified via the entity database 120 and / or other databases. In some embodiments, the points of interest engine 105 may determine multiple points of interest from the content of the source. For example, the points of interest engine 105 may determine multiple locations of a restaurant as points of interest based on identifying a single reference to the name of a restaurant in the content.

[0081] In step 710, additional information associated with the user is identified. In some embodiments, the additional information may come from the same source as the content used to determine the point of interest. For example, an email may be used to determine the point of interest and additional information from the email may be identified as the additional information, such as the sender of the message, the format of the terms in the message, and / or metadata associated with the message. In some embodiments, the additional information may be identified from one or more sources that are not used to determine the point of interest. For example, the content of the email may be used to determine the point of interest, and the additional information may be identified from other emails, the user's previous location information, the user's web history, and / or one or more additional content sources.

[0082] At step 715, based on the additional information, a relevance score for the point of interest is determined. The relevance score may be determined by a component that shares one or more characteristics with the relevance engine 115. In some embodiments, the relevance score may be a binary value. For example, the relevance score for the point of interest may be "relevant" or "not relevant," or another binary value. In some embodiments, the relevance score may be a relevance index, such as a value between 0 and 100.

[0083] In some embodiments, the relevance score may be based on a credibility measure of the source of the source of the additional information. For example, the relevance engine 115 may determine a relevance score indicating a point of interest determined from a calendar entry created by a user that is more relevant than a point of interest determined from an email from an unsolicited advertiser. In some embodiments, the relevance score may be determined based on the user's past location information. For example, the relevance engine 115 may determine the relevance score of the point of interest based on the frequency of the user's visits to the point of interest, the recency of the user's last visit to the location, and / or the length of the user's one or more visits to the point of interest. In some embodiments, the relevance score may be determined based on the prominence of one or more terms related to the point of interest in the source. For example, the relevance engine 115 may determine a relevance score indicating a point of interest mentioned in the title of the email that is more relevant than a point of interest included in the body of the email. At the same time, for example, the relevance score may be determined based on the format of the term in the source.

[0084] In some embodiments, the current time may be utilized to determine the relevance score for the point of interest. For example, a time may be identified as being relevant to the point of interest, and the relevance score may be determined based on the time between the current time and the identified relevant time. As the time associated with the point of interest approaches, it may be determined that the relevance score becomes more indicative of greater relevance. In some embodiments, as previously described, one or more additional factors may be utilized to determine the relevance score.

[0085] In step 720, point of interest information is provided based on the relevance score. In some embodiments, the point of interest information can be provided via a mapping application. For example, a map including indications of one or more determined points of interest can be provided to a user. In some embodiments, points of interest can be provided via a mapping application only when the associated relevance score meets a threshold. For example, the relevance engine 115 can determine a binary relevance score for a point of interest and provide an indication of a point of interest only when the point of interest is determined to be "relevant." In some embodiments, points of interest can be provided on a map with a prominence related to the determined relevance score. For example, the size of the indication of a point of interest on a map can be related to the determined relevance score of the point of interest, wherein the point of interest can appear larger than a point of interest having a relevance score indicating less relevance.

[0086] In some embodiments, the point of interest information may be provided to the user via a list of one or more points of interest. For example, a list of multiple points of interest within a threshold distance from the user may be provided to the user. In some embodiments, the ordering of the one or more points of interest in the list may be based on a determined relevance score of the point of interest. For example, the point of interest appears higher in the list of points of interest than a point of interest having a determined relevance score indicating less relevance. At the same time, for example, a point of interest is provided in the list only if the determined relevance score of the point of interest meets a threshold value.

[0087] Figure 8 810. The computer system 810 generally includes at least one processor 814, which communicates with a plurality of peripheral devices via a bus subsystem 812. These peripheral devices may include a storage subsystem 824, which includes, for example, a memory subsystem 828 and a file storage subsystem 826, a user interface input device 822, a user interface output device 820, and a network interface subsystem 816. The input and output devices allow a user to interact with the computer system 810. The network interface subsystem 816 provides an interface to an external network and is coupled to corresponding interface devices in other computer systems.

[0088] The user interface input device 822 may include a keyboard, a pointing device such as a mouse, trackball, touch pad, or graphic tablet, a scanner, a touch screen integrated into a display, an audio input device such as a voice recognition system, a microphone, and / or other types of input devices. In general, the use of the term "input device" is intended to include all possible types of devices and ways to input information into the computer system 810 or over a communication network.

[0089] User interface output device 820 can include display subsystem, printer, fax machine, or non-visual display such as audio output device.Display subsystem can include cathode ray tube (CRT), flat panel device such as liquid crystal display (LCD), projection device, or some other mechanisms for creating visible images.This display subsystem can also provide non-visual display via such as audio output device.Usually, use term " output device " is intended to include equipment and mode of all possible types from computer system 810 to user or another machine or computer system output information.

[0090] The storage subsystem 824 stores programs and data structures that provide the functionality of some or all of the modules described herein. For example, the storage subsystem 824 may include logic for determining points of interest from content from one or more sources associated with a user. As another example, the storage subsystem 824 may include logic for determining a relevance score for a point of interest based on additional information associated with a user.

[0091] These software modules are usually executed by processor 814 alone or in combination with other processors. The memory subsystem 828 used in the storage subsystem may include a variety of memories, including a main random access memory (RAM) 830 for storing instructions and data during program execution and a read-only memory (ROM) 832 for storing fixed instructions therein. The file storage subsystem 826 may provide persistent storage for programs and data files, and may include a hard drive, a floppy disk drive, a CD-ROM drive, an optical drive, or a removable media cartridge with associated removable media. The modules implementing the functions of certain embodiments may be stored in the storage subsystem 824 by the file storage subsystem 824, or may be stored in other machines accessible to the processor 814.

[0092] The bus subsystem 812 provides a mechanism for the various components and subsystems of the computer system 810 to communicate with each other as desired. Although the bus subsystem 812 is shown schematically as a single bus, alternative implementations of the bus subsystem may use multiple busses.

[0093] Computer system 810 can be of various types, including workstations, servers, computing clusters, blade servers, server farms, or any other data processing system or computing device. Due to the ever-changing nature of computers and networks, Figure 8 The description of the computer system 810 depicted in FIG. 8 is intended only as a specific example for illustrating some embodiments. Many other configurations of the computer system 810 are possible, which have more Figure 8 The computer systems depicted may have additional or fewer components.

[0094] Although various embodiments have been described and illustrated herein, various other devices and / or structures for performing the functions described herein and / or obtaining the results and / or one or more advantages thereof may be utilized, and each such variation and / or modification is intended to be within the scope of the embodiments described herein. More generally, all parameters, dimensions, materials, and configurations described herein are intended to be exemplary, and the actual parameters, dimensions, materials, and / or configurations will depend on one or more specific applications for which the teaching is used. A person skilled in the art will recognize or be able to confirm many specific embodiments equivalent to those described herein using only conventional experiments. Therefore, it is to be understood that the above embodiments are given only as examples, and within the scope of the attached claims and their equivalents, the embodiments may be practiced in a manner different from that specifically described and claimed. The embodiments of the present disclosure are directed to each individual feature, system, article, material, kit, and / or method described herein. In addition, any combination of two or more such features, systems, articles, materials, kits, and / or methods is included within the scope of the present disclosure when such features, systems, articles, materials, kits, and / or methods do not conflict with each other.

Claims

1. A method implemented by one or more processors, comprising: determining a first location having a first entity category from content of an electronic communication sent to a user; determining the point of interest having the second entity category based on a mapping between the first entity category corresponding to the first location and a second entity category corresponding to a point of interest in an electronic source external to the content, wherein the point of interest is a physical location, and wherein the first location does not have the second entity category, and the point of interest does not have the first entity category; identifying a time indication from content of the electronic communication sent to the user, the time indication being associated with the first location, and the time indication being one or both of a specific date and a specific time; The relevance score of the point of interest is determined based on the following two aspects: the distance between the point of interest and the first location, and the time indication associated with the first position; and A visual indication of the point of interest is provided based on the relevance score, the visual indication being provided for display to the user in a rendered map via a mapping application.

2. The method of claim 1, wherein: Providing the visual indication of the point of interest includes providing the time indication associated with the first location in addition to the visual indication of the point of interest to display the time indication to the user in the rendered map.

3. The method of claim 1, further comprising: determining an additional distance between a second location and the point of interest; Wherein, determining the relevance score of the point of interest is further based on the additional distance.

4. The method of claim 3, further comprising: The second location is determined from the content of the electronic communication, the second location having a third entity category and not having the first entity category or the second entity category.

5. The method of claim 3, wherein: The second location has a third entity class and does not have the first entity class or the second entity class.

6. The method of claim 1, wherein: Providing based on the relevance score includes determining a prominence level of the visual indication based on the relevance score.

7. A system comprising: At least one network interface; a memory for storing instructions; one or more processors configured to execute the instructions stored in the memory, wherein, when executing the instructions, the one or more processors will: determining a first location having a first entity category from content of an electronic communication sent to a user; determining the point of interest having the second entity category based on a mapping between the first entity category corresponding to the first location and a second entity category corresponding to a point of interest in an electronic source external to the content and accessible via the at least one network interface, wherein the point of interest is a physical location, and wherein the first location does not have the second entity category, and the point of interest does not have the first entity category; identifying a time indication from content of the electronic communication sent to the user, the time indication being associated with the first location, and the time indication being one or both of a specific date and a specific time; The relevance score of the point of interest is determined based on the following two aspects: the distance between the point of interest and the first location, and the time indication associated with the first position; and A visual indication of the point of interest is provided based on the relevance score, the visual indication being provided for display to the user in a rendered map via a mapping application.

8. The system of claim 7, wherein: When providing the visual indication of the point of interest, one or more of the processors will provide, in addition to the visual indication of the point of interest, the time indication associated with the first location for display to the user in the rendered map.

9. The system of claim 7, wherein: When executing the instructions, one or more of the processors will further: determining an additional distance between a second location and the point of interest; Wherein, when determining the relevance score of the point of interest, one or more of the processors will further determine the relevance score based on the additional distance.

10. The system of claim 9, wherein: When executing the instructions, one or more of the processors will further: The second location is determined from the content of the electronic communication, the second location having a third entity category and not having the first entity category or the second entity category.

11. The system of claim 9, wherein: The second location has a third entity class and does not have the first entity class or the second entity class.

12. The system of claim 7, wherein: In providing the visual indication of the point of interest, one or more of the processors will determine a prominence level of the visual indication when providing based on the relevance score.

13. At least one non-transitory computer-readable storage medium storing instructions executable by a processor, the instructions comprising instructions for: determining a first location having a first entity category from content of an electronic communication sent to a user; determining the point of interest having the second entity category based on a mapping between the first entity category corresponding to the first location and a second entity category corresponding to a point of interest in an electronic source external to the content, in, The point of interest is a physical location, and wherein the first location does not have the second entity category, and the point of interest does not have the first entity category; identifying a time indication from the content of the electronic communication, the time indication being associated with the first location, and the time indication being one or both of a specific date and a specific time; The relevance score of the point of interest is determined based on the following two aspects: the distance between the point of interest and the first location, and the time indication associated with the first position; and A visual indication of the point of interest is provided based on the relevance score, the visual indication being provided for display to the user in a rendered map via a mapping application.

14. The at least one non-transitory computer-readable storage medium of claim 13, wherein: The instructions for providing the visual indication of the point of interest include instructions for providing the time indication associated with the first location in addition to the visual indication of the point of interest for display to the user in the rendered map.

15. The at least one non-transitory computer-readable storage medium of claim 13, the instructions further comprising instructions for: determining an additional distance between a second location and the point of interest; in, The instructions for determining the relevance score for the point of interest include instructions for determining the relevance score further based on the additional distance.

16. The at least one non-transitory computer-readable storage medium of claim 13, wherein: The instructions for providing the visual indication of the point of interest include instructions for providing the point of interest with a prominence level based on the relevance score.

17. A method implemented by one or more processors, comprising: determining a first location having a first entity category from content of an electronic communication sent to a user; identifying a time indication from content of the electronic communication sent to the user, the time indication being associated with the first location, and the time indication being one or both of a specific date and a specific time; determining at least a first point of interest having a second entity category and a second point of interest also having a second entity category, wherein determining the first point of interest and the second point of interest is based on a mapping between the first entity category corresponding to the first location and the second entity category corresponding to the first point of interest and the second point of interest, wherein the first point of interest is a physical location, wherein the second point of interest is an additional physical location, and wherein the first location does not have the second entity category, the first point of interest does not have the first entity category, and the second point of interest does not have the first entity category; causing the first point of interest and the second point of interest to be output via a client device of the user, wherein causing the first point of interest and the second point of interest to be output is based on: a first distance between the first point of interest and the first location, a second distance between the second point of interest and the first location, and The time indication associated with the first position.

18. The method of claim 17, wherein: Causing the first point of interest and the second point of interest to be output includes causing the first point of interest and the second point of interest to be output in a list.

19. The method of claim 18, wherein: Causing the first point of interest and the second point of interest to be output based on the first distance, the second distance, and the time indication includes: determining a first relevance score for the first point of interest based on the first distance and the time indication; determining a second relevance score for the second point of interest based on the second distance and the time indication; and The first point of interest and the second point of interest are caused to be included in the list based on the first relevance score and the second relevance score.

20. The method of claim 19, wherein: Causing the first point of interest and the second point of interest to be included in the list based on the first relevance score and the second relevance score comprises: An order of the first point of interest and the second point of interest in the list is determined based on the first relevance score and the second relevance score.

21. The method of claim 17, wherein: Causing the first point of interest and the second point of interest to be output via the client device of the user comprises: The visual indication of the first point of interest and an additional visual indication of the second point of interest are caused to be provided for display to the user in the rendered map.

22. The method of claim 17, further comprising: The time indication associated with the first location is caused to be output in addition to the first point of interest and the second point of interest.

23. The method of claim 17, wherein: Causing the first point of interest and the second point of interest to be output based on the first distance, the second distance, and the time indication includes: determining a first relevance score for the first point of interest based on the first distance and the time indication; determining a second relevance score for the second point of interest based on the second distance and the time indication; and The first point of interest and the second point of interest are caused to be output based on the first relevance score satisfying a threshold and the second relevance score satisfying the threshold.

24. The method of claim 17, further comprising: determining a first additional distance between a second location and the first point of interest; as well as determining a second additional distance between the second location and the second point of interest; Wherein, causing the first point of interest and the second point of interest to be output is further based on the first additional distance and the second additional distance.

25. The method of claim 24, further comprising: The second location is determined from the content of the electronic communication, the second location having a third entity category and not having the first entity category or the second entity category.

26. A system comprising: At least one network interface; a memory for storing instructions; one or more processors configured to execute the instructions stored in the memory, wherein, when executing the instructions, the one or more processors will: determining a first location having a first entity category from content of an electronic communication sent to a user; identifying a time indication from content of the electronic communication sent to the user, the time indication being associated with the first location, and the time indication being one or both of a specific date and a specific time; Determine at least the following based on a mapping between the first entity category corresponding to the first location and the second entity category corresponding to the first point of interest and the second point of interest: the first point of interest having the second entity category, and also having said second point of interest of said second entity category, wherein the first point of interest is a physical location, wherein the second point of interest is an additional physical location, and wherein the first location does not have the second entity category, the first point of interest does not have the first entity category, and the second point of interest does not have the first entity category; causing the first point of interest and the second point of interest to be output via a client device of the user based on: a first distance between the first point of interest and the first location, a second distance between the second point of interest and the first location, and The time indication associated with the first position.

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