User event tag generation method, device, storage medium, and apparatus

Abstract

The application discloses a user event label generation method and device, a storage medium and an apparatus, and relates to the technical field of event label generation. The method comprises the following steps: acquiring crowd gathering event information, determining a to-be-verified gathering crowd according to the crowd gathering event information, acquiring a user portrait of each user in the to-be-verified gathering crowd, screening the to-be-verified gathering crowd according to the user portrait and the crowd gathering event information, obtaining an actual gathering crowd, and generating an event label of each user in the actual gathering crowd according to the crowd gathering event information. Compared with the prior art, the application can automatically acquire crowd gathering event information, determine an actual gathering crowd based on the crowd gathering event information and a user portrait, and generate an event label of each user in the actual gathering crowd according to the crowd gathering event information, so that the real-time automatic generation of the event label is realized, and the generation efficiency of the event label is improved.

Description

Technical Field

[0001] This invention relates to the field of computer technology, and in particular to a method, apparatus, storage medium, and device for generating user event tags. Background Technology

[0002] With the development of mobile internet and big data technologies, operators' data is becoming increasingly complex, and customer needs are becoming more diversified. Traditional operational approaches can no longer meet competitive demands, and it is necessary to shift from a business-centric to a customer-centric approach. By building a mature and comprehensive tagging system, we can accurately describe customer characteristics, achieve a comprehensive analysis and understanding of customer needs, provide differentiated information services to customers, and enhance the value of customer insights.

[0003] In the process of building a tagging system, in addition to describing the basic characteristics of customers such as spending power, social attributes, social behavior, terminal characteristics, location characteristics, online behavior, personality and emotions, there is another type of tag that describes customers’ behavior in response to major events, namely event tags, which are of great significance in customer behavior insight and value realization.

[0004] Event tags mainly include clustering event tags, such as attending concerts and football matches, and sports event tags, such as participating in marathons and traveling during holidays. Current event tags primarily rely on manual event identification and tag development, meaning that event information is obtained manually, event characteristics are analyzed, tagging programs are developed, and event tags are constructed.

[0005] However, the above methods have the following problems: 1. High degree of manual intervention: Whether it is obtaining event information or analyzing event characteristics, it requires manual intervention, resulting in a large workload and low automation. 2. Poor reusability of the tag construction process: Even for the same type of event tags, it is necessary to collect event information again, analyze event characteristics, and then redevelop the tag program based on the tag information and tag characteristics to build event tags. 3. Large amount of repetitive work: Due to the special nature of event tag construction, each event is treated independently, lacking automated processes and fixed patterns. With personnel changes, event tag construction needs to be restarted and repeated, resulting in a large overall workload. 4. Low timeliness: Current tag construction is mainly based on offline data, resulting in low timeliness and inability to quickly respond to customers' real-time needs.

[0006] The above content is only used to help understand the technical solution of the present invention and does not represent an admission that the above content is prior art. Summary of the Invention

[0007] The main objective of this invention is to provide a method, device, storage medium, and apparatus for generating user event tags, aiming to solve the technical problems in the prior art where manually creating event tags requires a large amount of manual intervention, cannot be copied, has low timeliness, and involves a large workload.

[0008] To achieve the above objectives, the present invention provides a method for generating user event tags, the method comprising the following steps:

[0009] Obtain information on crowd gathering events, and determine the crowd to be verified based on the crowd gathering event information;

[0010] Obtain the user profile of each user in the population to be verified;

[0011] The actual crowd is obtained by filtering the crowd to be verified based on the user profile and the crowd gathering event information;

[0012] Based on the crowd gathering event information, event tags are generated for each user in the actual crowd gathering.

[0013] Optionally, the step of obtaining crowd gathering event information and determining the crowd to be verified based on the crowd gathering event information specifically includes:

[0014] Crawl hot topic information from preset websites and determine crowd gathering event information based on the hot topic information;

[0015] Extract the locations of crowd gatherings from the crowd gathering event information, and match these locations with POI information on the map;

[0016] The clustering area is determined based on the matching results, and the corresponding communication base station is located within the clustering area;

[0017] The communication data of the communication base station is obtained, and the population to be verified is determined based on the communication data.

[0018] Optionally, the step of obtaining crowd gathering event information and determining the crowd to be verified based on the crowd gathering event information specifically includes:

[0019] Obtain pedestrian flow detection information, and determine the detection area and the pedestrian flow in the detection area based on the pedestrian flow detection information;

[0020] The presence of crowds in the detection area is determined based on the pedestrian flow.

[0021] When there is a crowd gathering in the detection area, search for the crowd gathering event information corresponding to the detection area;

[0022] The crowd gathering information and the crowd detection information are used to determine the crowd to be verified.

[0023] Optionally, the step of filtering the crowd to be verified based on the user profile and the crowd gathering event information to obtain the actual crowd includes:

[0024] The event name of the crowd gathering event is determined based on the crowd gathering event information;

[0025] The crowd gathering events are classified according to the event names to obtain the event categories corresponding to the crowd gathering events. The event categories include movement pattern events and fixed pattern events.

[0026] Search the preset model library for the event handling model corresponding to the motion pattern event or the fixed pattern event;

[0027] The users to be verified are filtered based on the user profile, the crowd gathering event information, and the event processing model to obtain the actual gathered users.

[0028] Optionally, the step of filtering the users to be verified based on the user profile, the crowd gathering event information, and the event processing model to obtain the actual gathered users specifically includes:

[0029] Obtain the user location of each user in the aggregated population to be verified and the detection time corresponding to the user location;

[0030] Extract event location information and event time information from the crowd gathering event information;

[0031] The actual cluster of people to be verified is obtained by filtering the user's location, the detection time corresponding to the user's location, the event location information, the event time information, the user profile, and the event processing model.

[0032] Optionally, after the step of generating event tags for each user in the actual crowd based on the crowd gathering event information, the user event tag generation method further includes:

[0033] Upon receiving an event tag query request, the event tag query request is parsed to obtain the event number and user number;

[0034] The target cluster event is determined based on the event number and the user number, and the event information of the target cluster event is obtained.

[0035] Optionally, after the step of generating event tags for each user in the actual crowd based on the crowd gathering event information, the user event tag generation method further includes:

[0036] Obtain business requirement information and generate requirement tags to be combined based on the business requirement information;

[0037] User marketing tags are generated based on the demand tags to be combined and the event tags, and the user marketing tags are sent to the preset marketing terminal.

[0038] Furthermore, to achieve the above objectives, the present invention also proposes a user event tag generation device, which includes a memory, a processor, and a user event tag generation program stored in the memory and executable on the processor. The user event tag generation program is configured to implement the steps of the user event tag generation method described above.

[0039] In addition, to achieve the above objectives, the present invention also proposes a storage medium storing a user event tag generation program, wherein when the user event tag generation program is executed by a processor, it implements the steps of the user event tag generation method described above.

[0040] In addition, to achieve the above objectives, the present invention also proposes a user event tag generation device, which includes: an acquisition module, a filtering module and a generation module;

[0041] The acquisition module is used to acquire information on crowd gathering events and determine the crowd to be verified based on the crowd gathering event information.

[0042] The acquisition module is also used to acquire user profiles of each user in the population to be verified;

[0043] The filtering module is used to filter the crowd to be verified based on the user profile and the crowd gathering event information to obtain the actual crowd.

[0044] The generation module is used to generate event tags for each user in the actual crowd based on the crowd gathering event information.

[0045] This invention acquires information on crowd gathering events, determines the crowd to be verified based on this information, obtains user profiles for each user within the crowd, filters the crowd based on these profiles and the crowd gathering event information, obtains the actual crowd, and generates event tags for each user within the actual crowd based on the crowd gathering event information. Compared to existing methods of manually creating event tags, this invention automatically acquires crowd gathering event information, determines the actual crowd based on this information and user profiles, and generates event tags for each user within the actual crowd, thereby achieving real-time automatic generation of event tags and improving the efficiency of event tag generation. Attached Figure Description

[0046] Figure 1 This is a schematic diagram of the structure of the user event tag generation device in the hardware operating environment involved in the embodiments of the present invention;

[0047] Figure 2 This is a flowchart illustrating the first embodiment of the user event tag generation method of the present invention;

[0048] Figure 3 This is a flowchart illustrating the second embodiment of the user event tag generation method of the present invention;

[0049] Figure 4 This is a flowchart illustrating the third embodiment of the user event tag generation method of the present invention;

[0050] Figure 5 This is a structural block diagram of the first embodiment of the user event tag generation device of the present invention.

[0051] The realization of the objective, functional features and advantages of the present invention will be further explained in conjunction with the embodiments and with reference to the accompanying drawings. Detailed Implementation

[0052] It should be understood that the specific embodiments described herein are merely illustrative of the invention and are not intended to limit the invention.

[0053] Reference Figure 1 , Figure 1 This is a schematic diagram of the user event tag generation device structure in the hardware operating environment involved in the embodiments of the present invention.

[0054] like Figure 1As shown, the user event tag generation device may include: a processor 1001, such as a central processing unit (CPU), a communication bus 1002, a user interface 1003, a network interface 1004, and a memory 1005. The communication bus 1002 is used to enable communication between these components. The user interface 1003 may include a display screen, and optionally, it may also include a standard wired interface or a wireless interface. In this invention, the wired interface of the user interface 1003 may be a USB interface. The network interface 1004 may optionally include a standard wired interface or a wireless interface (such as a Wi-Fi interface). The memory 1005 may be a high-speed random access memory (RAM) or a non-volatile memory (NVM), such as a disk drive. The memory 1005 may also optionally be a storage device independent of the aforementioned processor 1001.

[0055] Those skilled in the art will understand that Figure 1 The structure shown does not constitute a limitation on the user event tag generating device and may include more or fewer components than shown, or combine certain components, or have different component arrangements.

[0056] like Figure 1 As shown, the memory 1005, which is identified as a computer storage medium, may include an operating system, a network communication module, a user interface module, and a user event tag generation program.

[0057] exist Figure 1 In the user event tag generation device shown, the network interface 1004 is mainly used to connect to the backend server and communicate data with the backend server; the user interface 1003 is mainly used to connect to the user equipment; the user event tag generation device calls the user event tag generation program stored in the memory 1005 through the processor 1001 and executes the user event tag generation method provided in the embodiment of the present invention.

[0058] Based on the above hardware structure, an embodiment of the user event tag generation method of the present invention is proposed.

[0059] Reference Figure 2 , Figure 2 This is a flowchart illustrating the first embodiment of the user event tag generation method of the present invention, which presents the first embodiment of the user event tag generation method of the present invention.

[0060] Step S10: Obtain information on crowd gathering events and determine the crowd to be verified based on the crowd gathering event information.

[0061] It should be understood that the execution subject of this embodiment can be the aforementioned user event tag generating device. The user event tag generating device can be a computing service device with data processing, network communication and program running functions, such as a server and a computer. The execution subject can also be other electronic devices that can achieve the same or similar functions. This embodiment does not limit this. In this embodiment and the following embodiments, the user event tag generating device is used as an example to describe the user event tag generating method of the present invention.

[0062] It should be noted that a mass gathering event can be an event in which a large number of users gather at a certain location within a certain time period. For example, watching a concert, watching a football match, participating in a marathon, and traveling during holidays.

[0063] Information about crowd gathering events can include the name of the event, the location of the gathering, and the time of the gathering.

[0064] It is understandable that obtaining information on crowd gathering events can involve crawling information on trending events from the internet and determining crowd gathering event information based on the trending event information;

[0065] Alternatively, it can obtain the pedestrian flow in the detection area, determine whether there is a crowd gathering in the detection area based on the pedestrian flow, and if there is a crowd gathering in the detection area, search for the corresponding crowd gathering event information in the detection area;

[0066] It can also receive user-uploaded requests for reporting gathering events and determine the information about the gathering events based on these requests. This embodiment does not impose any limitations on this.

[0067] It should be noted that the cluster of people to be verified may be those initially identified as a cluster, but further verification is still required.

[0068] It should be understood that determining the population to be verified based on information about crowd gathering events can mean determining the area where crowds gather based on the information about crowd gathering events, and then taking users in the area where crowds gather as the population to be verified.

[0069] Step S20: Obtain the user profile of each user in the population to be verified.

[0070] It should be noted that user profiles can include user data, communication behavior, and internet browsing behavior, etc.

[0071] Understandably, obtaining user profiles for each user in the group to be verified can be achieved by searching for the corresponding user profile in a pre-set database. This pre-set database contains the correspondence between each user in the group and their corresponding user profile, and this correspondence can be pre-entered by the administrator of the user event tag generation device.

[0072] Step S30: Filter the crowd to be verified based on the user profile and the crowd gathering event information to obtain the actual crowd.

[0073] It should be understood that in practical applications, there may be instances where users accidentally pass through a gathering area and are counted as part of the gathering population. Therefore, it is necessary to screen the gathering population to be verified in order to determine the actual gathering population.

[0074] It is understandable that filtering the crowd to be verified based on user profiles and crowd gathering event information to obtain the actual crowd can involve identifying non-event groups based on user profiles and crowd gathering event information, and then removing non-event groups from the crowd to be verified to obtain the actual crowd. Here, non-event groups may be those who were mistakenly identified as part of a crowd in the initial assessment.

[0075] In practical implementation, for example, if the crowd gathering event is a marathon, and the user profile of user A, who is identified as a crowd to be verified, is that he does not exercise frequently, then user A can be determined to be a non-event group and needs to be removed from the crowd to be verified.

[0076] Step S40: Generate event tags for each user in the actual crowd based on the crowd gathering event information.

[0077] It should be noted that event tags are used to identify information such as the event number, user number, event type, event content, event object, start time, end time, event location, and latitude and longitude.

[0078] It should be understood that generating event tags for each user in the actual crowd based on crowd gathering event information can be achieved by aggregating crowd gathering event information and user information of each user in the actual crowd to obtain event tags.

[0079] Furthermore, to facilitate administrators in querying user event tags, step S40 further includes:

[0080] Upon receiving an event tag query request, the event tag query request is parsed to obtain the event number and user number;

[0081] The target cluster event is determined based on the event number and the user number, and the event information of the target cluster event is obtained.

[0082] It should be noted that the event tag query request can be entered by the administrator through the user interface of the user event tag generation device; or it can be entered by the administrator through a terminal device. The terminal device can establish a communication connection with the user event tag generation device in advance, and the terminal device can send the event tag query request entered by the administrator to the user event tag generation device.

[0083] It should be understood that determining the target clustered event based on the event number and user number can be achieved by generating query information based on the event number and user number, and then searching for the target clustered event corresponding to the query information in a preset tag library. The preset tag library contains the correspondence between query information and clustered events, and this correspondence can be automatically entered when generating the user's event tags.

[0084] It should be noted that event information may include event type, event content, event target, start time, end time, event location, longitude and latitude, etc.

[0085] Furthermore, in order to enable marketing based on event tags, after step S40, the method further includes:

[0086] Obtain business requirement information and generate requirement tags to be combined based on the business requirement information;

[0087] User marketing tags are generated based on the demand tags to be combined and the event tags, and the user marketing tags are sent to the preset marketing terminal.

[0088] It should be noted that business requirement information can include information such as gender, business preferences, and application preferences.

[0089] It should be understood that business requirement information can be obtained through business requests. These requests can be initiated by pre-set marketing terminals, which can establish a communication connection with the user event tag generation device beforehand.

[0090] It is understandable that generating user marketing tags based on demand tags and event tags can involve fusing information from demand tags and event tags to obtain user marketing tags.

[0091] This embodiment acquires information about crowd gathering events, determines the crowd to be verified based on this information, obtains user profiles for each user in the crowd to be verified, filters the crowd to be verified based on the user profiles and the crowd gathering event information, obtains the actual crowd, and generates event tags for each user in the actual crowd based on the crowd gathering event information. Compared to existing methods of manually creating event tags, this invention can automatically acquire crowd gathering event information, determine the actual crowd based on the crowd gathering event information and user profiles, and generate event tags for each user in the actual crowd, thereby achieving real-time automatic generation of event tags and improving the efficiency of event tag generation.

[0092] Reference Figure 3 , Figure 3 This is a flowchart illustrating the second embodiment of the user event tag generation method of the present invention, based on the above. Figure 2 The first embodiment shown presents a second embodiment of the user event tag generation method of the present invention.

[0093] In the second embodiment, step S10 includes:

[0094] Step S101: Crawl hot event information from a preset website and determine crowd gathering event information based on the hot event information.

[0095] It should be noted that the preset websites can be pre-set by the administrators of the user event tag generation device according to actual needs. For example, ticketing websites, official competition websites, and official conference websites can be set as preset websites.

[0096] Trending events can include concerts, marathons, internet conferences, and the Yunqi Conference. Information about trending events can include the event name, time, and location.

[0097] It should be understood that crawling hot topic information from a preset website can be done by using a preset script to crawl the website's traffic and search volume, and then determining the hot topic information based on the traffic and search volume.

[0098] It should be noted that the preset script can be used to crawl information on the Internet. The crawling scope of the preset script can be preset by the administrator of the user event tag generation device according to actual needs. The preset script can be a web crawler script, etc.

[0099] It is understandable that determining crowd gathering information based on trending event information can involve determining the number of people gathered based on trending event information, identifying trending events with a number of people exceeding a preset threshold as crowd gathering events, and using the corresponding trending event information as crowd gathering event information. The preset threshold can be pre-set by the administrator of the user event tag generation device according to actual needs.

[0100] Step S102: Extract the location of the crowd gathering from the crowd gathering event information, and match the location of the crowd gathering with the map POI information.

[0101] It should be understood that extracting crowd gathering locations from crowd gathering event information can involve obtaining information identifiers and then extracting the crowd gathering locations from the crowd gathering event information based on these information identifiers. Here, the information identifiers are used to identify the information content.

[0102] It should be noted that map POI information can be map Point of Interest (POI) information. In a geographic information system, a map POI can be a building, a shop, a mailbox, or a bus stop, etc.

[0103] Step S103: Determine the clustering area based on the matching results, and find the communication base station corresponding to the clustering area.

[0104] Understandably, determining the clustered area based on the matching results could mean taking the area corresponding to the successfully matched map POI information as the clustered area.

[0105] It should be understood that finding the corresponding communication base station for a clustered area can be done by searching a preset base station table. This preset base station table contains the correspondence between areas and communication base stations, which can be pre-entered by the administrator of the user event tag generation device.

[0106] Step S104: Obtain the communication data of the communication base station, and determine the crowd to be verified based on the communication data.

[0107] It should be noted that communication data can include communication location signaling and mobile network data.

[0108] It should be understood that by analyzing communication data, it is possible to determine which users have connected to the communication base station, and by matching the time of user connection with the time of crowd gathering, the crowd to be verified can be identified.

[0109] The second embodiment crawls hot topic event information from a preset website, determines crowd gathering event information based on the hot topic event information, extracts crowd gathering locations from the crowd gathering event information, matches the crowd gathering locations with map POI information, determines the gathering area based on the matching results, finds the communication base station corresponding to the gathering area, obtains the communication data of the communication base station, and determines the crowd to be verified based on the communication data. Thus, it can realize the automatic discovery of crowd gathering events through real-time network crawling, and by combining the communication base station data, it can preliminarily determine the crowd in the crowd gathering event.

[0110] In the second embodiment, step S10 further includes:

[0111] Step S101': Obtain pedestrian flow detection information, and determine the detection area and the pedestrian flow in the detection area based on the pedestrian flow detection information.

[0112] It should be noted that the pedestrian flow detection information can include the detection time, the detection area, and the pedestrian flow within that area. This information can be obtained through monitoring data uploaded by pre-set monitoring devices. These pre-set monitoring devices can establish a communication connection with a user event tag generation device beforehand, allowing them to upload monitoring information to the user event tag generation device via this connection. These pre-set monitoring devices can be, for example, real-time pedestrian flow monitoring cameras.

[0113] It should be understood that determining the detection area and the pedestrian flow within the detection area based on pedestrian flow detection information can be achieved by extracting information from the pedestrian flow detection information using information identifiers. Here, the information identifiers are used to identify the information content.

[0114] Step S102': Determine whether there is a crowd gathering in the detection area based on the pedestrian flow.

[0115] Understandably, determining whether there is crowd gathering in a detection area based on pedestrian flow can be done by checking if the pedestrian flow exceeds a preset threshold. If the pedestrian flow exceeds the preset threshold, crowd gathering is determined to exist in the detection area; if the pedestrian flow is less than or equal to the preset threshold, crowd gathering is determined to not exist in the detection area. The preset pedestrian flow threshold can be pre-set by the administrator of the user event tag generation device.

[0116] Step S103': When there is a crowd gathering in the detection area, search for the crowd gathering event information corresponding to the detection area.

[0117] It should be understood that the presence of crowds in the testing area indicates a potential crowd gathering event. Therefore, it is necessary to locate the crowd gathering event information corresponding to the testing area.

[0118] Understandably, finding information on crowd gathering events corresponding to a detection area can be achieved by crawling such information from pre-set websites. These pre-set websites can be configured by the administrators of the user event tag generation device according to actual needs. For example, ticketing websites, official competition websites, and official conference websites can be set as pre-set websites.

[0119] Step S104': Determine the crowd to be verified based on the crowd gathering event information and the crowd detection information.

[0120] It should be understood that determining the population to be verified based on information about crowd gathering events and crowd detection information can involve identifying the crowd gathering area based on the crowd gathering event information, identifying users in the crowd gathering area based on the crowd detection information, and then using these users as the population to be verified.

[0121] In practical implementation, for example, real-time pedestrian flow detection information for business district B is obtained. When the pedestrian flow in business district B exceeds the warning threshold for the same period, it is determined that there is a crowd gathering in business district B. At this time, the corresponding event information for business district B is searched through the Internet web crawler. If it is found that store C in business district B is having an anniversary event, then users in store C are identified as the crowd to be verified.

[0122] The second embodiment acquires pedestrian flow detection information and determines the detection area and pedestrian flow in the detection area based on the pedestrian flow detection information. It judges whether there is a crowd gathering in the detection area based on the pedestrian flow. When there is a crowd gathering in the detection area, it searches for the crowd gathering event information corresponding to the detection area. Based on the crowd gathering event information and pedestrian flow detection information, it determines the crowd to be verified. Thus, it can realize the automatic discovery of crowd gathering events through pedestrian flow detection, and can preliminarily determine the crowd gathering in the crowd gathering event through the crowd gathering event information.

[0123] Reference Figure 4 , Figure 4 This is a flowchart illustrating the third embodiment of the user event tag generation method of the present invention, based on the above. Figure 2 The first embodiment shown presents a third embodiment of the user event tag generation method of the present invention.

[0124] In the third embodiment, step S30 includes:

[0125] Step S301: Determine the event name of the crowd gathering event based on the crowd gathering event information.

[0126] It should be understood that determining the event name of a crowd gathering event based on crowd gathering event information can be done by extracting the event name from the crowd gathering event information.

[0127] Step S302: Classify the crowd gathering event according to the event name to obtain the event category corresponding to the crowd gathering event. The event category includes movement pattern events and fixed pattern events.

[0128] It should be noted that sports-themed events can include participating in a marathon and traveling during holidays. Fixed-themed events can include watching a concert and watching a football match.

[0129] It should be understood that classifying crowd gathering events based on event names to obtain the corresponding event categories can be achieved by matching event names with event keywords and determining the event category based on the matching results. Event keywords can be sports event keywords or fixed event keywords. Sports event keywords can include "sports" and "travel," while fixed event keywords can include "watching" and "meeting," etc.

[0130] Step S303: Search for the event handling model corresponding to the motion mode event or the fixed mode event in the preset model library.

[0131] It should be noted that the preset model library contains the correspondence between pattern events and event handling models. The correspondence between pattern events and event handling models can be preset by the administrator of the user event tag generation device.

[0132] In specific implementations, for example, the event processing model corresponding to a motion pattern event is a motion pattern processing model. Specifically, the motion pattern processing model analyzes the user's location movement trajectory within the time frame of the event, matches it with the location movement trajectory of a crowd gathering event, and determines whether the user participated in the motion pattern event based on the matching results and other characteristics.

[0133] The event handling model corresponding to a fixed-pattern event is the fixed-pattern processing model. Specifically, the fixed-pattern processing model analyzes whether the user's location trajectory matches the typical characteristics of a fixed event, and uses other user characteristics as supplementary information to determine whether the user participated in the fixed-pattern event.

[0134] Step S304: Based on the user profile, the crowd gathering event information, and the event processing model, filter the users to be verified to obtain the actual users gathered.

[0135] Understandably, the actual users to be verified are obtained by filtering users based on user profiles, crowd gathering event information, and event processing models. This can be achieved by obtaining the user location and corresponding detection time of each user in the crowd to be verified, extracting event location information and event time information from the crowd gathering event information, and filtering the crowd to be verified based on user location, corresponding detection time, event location information, event time information, user profiles, and event processing models.

[0136] In specific implementations, for example, when the crowd gathering event is a marathon, the system detects whether the user's location movement trajectory matches the marathon route, and whether the start and end times also match the marathon time. It also combines user behavior habits to determine whether the user has participated in the marathon event.

[0137] When the crowd gathering event is a concert, data analysis is used to determine whether a user stayed at the venue during the concert, and the user's online history, such as previous concert ticket purchases, is referenced to determine whether the user participated in the fixed pattern of attending a concert.

[0138] The third embodiment determines the event name of the crowd gathering event based on the crowd gathering event information, classifies the crowd gathering event according to the event name to obtain the event category corresponding to the crowd gathering event. The event category includes motion pattern events and fixed pattern events. The event processing model corresponding to motion pattern events or fixed pattern events is searched in the preset model library. Based on the user profile, crowd gathering event information and event processing model, the users to be verified are filtered to obtain the actual gathered users. Thus, different event processing models can be determined based on different crowd gathering events to eliminate non-event groups and determine the actual gathered group.

[0139] Furthermore, this embodiment of the invention also proposes a storage medium storing a user event tag generation program, which, when executed by a processor, implements the steps of the user event tag generation method described above.

[0140] In addition, refer to Figure 5 The present invention also proposes a user event tag generation device, which includes: an acquisition module 10, a filtering module 20 and a generation module 30;

[0141] The acquisition module 10 is used to acquire information on crowd gathering events and determine the crowd to be verified based on the crowd gathering event information.

[0142] It should be noted that a mass gathering event can be an event in which a large number of users gather at a certain location within a certain period of time. For example, watching a concert, watching a football match, participating in a marathon, and traveling during holidays.

[0143] Information about crowd gathering events can include the name of the event, the location of the gathering, and the time of the gathering.

[0144] It is understandable that obtaining information on crowd gathering events can involve crawling information on trending events from the internet and determining crowd gathering event information based on the trending event information;

[0145] Alternatively, it can obtain the pedestrian flow in the detection area, determine whether there is a crowd gathering in the detection area based on the pedestrian flow, and if there is a crowd gathering in the detection area, search for the corresponding crowd gathering event information in the detection area;

[0146] It can also receive user-uploaded requests for reporting gathering events and determine the information about the gathering events based on these requests. This embodiment does not impose any limitations on this.

[0147] It should be noted that the cluster of people to be verified may be those initially identified as a cluster, but further verification is still required.

[0148] It should be understood that determining the population to be verified based on information about crowd gathering events can mean determining the area where people gather based on the information about crowd gathering events, and then taking users in the area where people gather as the population to be verified.

[0149] The acquisition module 10 is also used to acquire user profiles of each user in the population to be verified.

[0150] It should be noted that user profiles can include user data, communication behavior, and internet browsing behavior, etc.

[0151] Understandably, obtaining user profiles for each user in the group to be verified can be achieved by searching for the corresponding user profile in a pre-set database. This pre-set database contains the correspondence between each user in the group and their corresponding user profile, and this correspondence can be pre-entered by the administrator of the user event tag generation device.

[0152] The filtering module 20 is used to filter the crowd to be verified based on the user profile and the crowd gathering event information to obtain the actual crowd.

[0153] It should be understood that in practical applications, there may be instances where users accidentally pass through a gathering area and are counted as part of the gathering population. Therefore, it is necessary to screen the gathering population to be verified in order to determine the actual gathering population.

[0154] It is understandable that filtering the crowd to be verified based on user profiles and crowd gathering event information to obtain the actual crowd can involve identifying non-event groups based on user profiles and crowd gathering event information, and then removing non-event groups from the crowd to be verified to obtain the actual crowd. Here, non-event groups may be those who were mistakenly identified as part of a crowd in the initial assessment.

[0155] In practical implementation, for example, if the crowd gathering event is a marathon, and the user profile of user A, who is identified as a crowd to be verified, is that he does not exercise frequently, then user A can be determined to be a non-event group and needs to be removed from the crowd to be verified.

[0156] The generation module 30 is used to generate event tags for each user in the actual crowd based on the crowd gathering event information.

[0157] It should be noted that event tags are used to identify information such as the event number, user number, event type, event content, event object, start time, end time, event location, and latitude and longitude.

[0158] It should be understood that generating event tags for each user in the actual crowd based on crowd gathering event information can be achieved by aggregating crowd gathering event information and user information of each user in the actual crowd to obtain event tags.

[0159] Furthermore, to facilitate administrators in querying user event tags, the user event tag generation device further includes a query module;

[0160] The query module is used to parse the event tag query request when it receives the event tag query request, so as to obtain the event number and user number, determine the target cluster event based on the event number and user number, and obtain the event information of the target cluster event.

[0161] It should be noted that the event tag query request can be entered by the administrator through the user interface of the user event tag generation device; or it can be entered by the administrator through a terminal device. The terminal device can establish a communication connection with the user event tag generation device in advance, and the terminal device can send the event tag query request entered by the administrator to the user event tag generation device.

[0162] It should be understood that determining the target clustered event based on the event number and user number can be achieved by generating query information based on the event number and user number, and then searching for the target clustered event corresponding to the query information in a preset tag library. The preset tag library contains the correspondence between query information and clustered events, and this correspondence can be automatically entered when generating the user's event tags.

[0163] It should be noted that event information may include event type, event content, event target, start time, end time, event location, longitude and latitude, etc.

[0164] Furthermore, in order to enable marketing based on event tags, the user event tag generation device also includes: a demand module;

[0165] The demand module is used to acquire business demand information, generate demand tags to be combined based on the business demand information, generate user marketing tags based on the demand tags to be combined and the event tags, and send the user marketing tags to a preset marketing terminal.

[0166] It should be noted that business requirement information can include information such as gender, business preferences, and application preferences.

[0167] It should be understood that business requirement information can be obtained through business requests. These requests can be initiated by pre-set marketing terminals, which can establish a communication connection with the user event tag generation device beforehand.

[0168] It is understandable that generating user marketing tags based on demand tags and event tags can involve fusing information from demand tags and event tags to obtain user marketing tags.

[0169] This embodiment acquires information about crowd gathering events, determines the crowd to be verified based on this information, obtains user profiles for each user in the crowd to be verified, filters the crowd to be verified based on the user profiles and the crowd gathering event information, obtains the actual crowd, and generates event tags for each user in the actual crowd based on the crowd gathering event information. Compared to existing methods of manually creating event tags, this invention can automatically acquire crowd gathering event information, determine the actual crowd based on the crowd gathering event information and user profiles, and generate event tags for each user in the actual crowd, thereby achieving real-time automatic generation of event tags and improving the efficiency of event tag generation.

[0170] Other embodiments or specific implementations of the user event tag generation device described in this invention can be found in the above-described method embodiments, and will not be repeated here.

[0171] It should be noted that, in this document, the terms "comprising," "including," or any other variations thereof are intended to cover non-exclusive inclusion, such that a process, method, article, or system that comprises a list of elements includes not only those elements but also other elements not expressly listed, or elements inherent to such a process, method, article, or system. Unless otherwise specified, an element defined by the phrase "comprising one..." does not exclude the presence of other identical elements in the process, method, article, or system that includes that element.

[0172] The sequence numbers of the above embodiments of the present invention are for descriptive purposes only and do not represent the superiority or inferiority of the embodiments. In the unit claims listing several devices, several of these devices may be embodied by the same hardware item. The use of the terms first, second, and third, etc., does not indicate any order and can be interpreted as names.

[0173] Through the above description of the embodiments, those skilled in the art can clearly understand that the methods of the above embodiments can be implemented by means of software plus necessary general-purpose hardware platforms. Of course, they can also be implemented by hardware, but in many cases the former is a better implementation method. Based on this understanding, the technical solution of the present invention, or the part that contributes to the prior art, can be embodied in the form of a software product. This computer software product is stored in a storage medium (such as a read-only memory image (ROM) / random access memory (RAM), magnetic disk, optical disk), and includes several instructions to cause a terminal device (which may be a mobile phone, computer, server, air conditioner, or network device, etc.) to execute the methods described in the various embodiments of the present invention.

[0174] The above are merely preferred embodiments of the present invention and do not limit the scope of the patent. Any equivalent structural or procedural transformations made based on the description and drawings of the present invention, or direct or indirect applications in other related technical fields, are similarly included within the scope of patent protection of the present invention.

Claims

1. A method for generating user event tags, characterized in that, The method for generating user event tags includes the following steps: Obtain information on crowd gathering events and determine the crowd to be verified based on the crowd gathering event information, wherein the crowd gathering event information includes the name of the crowd gathering event, the location of the crowd gathering, and the time of the crowd gathering; Obtain user profiles for each user in the population to be verified, wherein the user profiles include user information, communication behavior, and internet browsing behavior; The actual crowd is obtained by filtering the crowd to be verified based on the user profile and the crowd gathering event information; Based on the crowd gathering event information, generate event tags for each user in the actual gathered crowd; The step of filtering the crowd to be verified based on the user profile and the crowd gathering event information to obtain the actual crowd includes: The event name of the crowd gathering event is determined based on the crowd gathering event information; The crowd gathering events are classified according to the event names to obtain the event categories corresponding to the crowd gathering events. The event categories include movement pattern events and fixed pattern events. Search the preset model library for the event handling model corresponding to the motion pattern event or the fixed pattern event; The actual crowd is obtained by filtering the crowd to be verified based on the user profile, the crowd gathering event information, and the event processing model.

2. The user event tag generation method as described in claim 1, characterized in that, The steps of acquiring crowd gathering event information and determining the crowd to be verified based on the crowd gathering event information specifically include: Crawl hot topic information from preset websites and determine crowd gathering event information based on the hot topic information; Extract the locations of crowd gatherings from the crowd gathering event information, and match these locations with POI information on the map; The clustering area is determined based on the matching results, and the corresponding communication base station is located within the clustering area; The communication data of the communication base station is obtained, and the population to be verified is determined based on the communication data.

3. The user event tag generation method as described in claim 1, characterized in that, The steps of acquiring crowd gathering event information and determining the crowd to be verified based on the crowd gathering event information specifically include: Obtain pedestrian flow detection information, and determine the detection area and the pedestrian flow in the detection area based on the pedestrian flow detection information; The presence of crowds in the detection area is determined based on the pedestrian flow. When there is a crowd gathering in the detection area, search for the crowd gathering event information corresponding to the detection area; The crowd gathering information and the crowd detection information are used to determine the crowd to be verified.

4. The user event tag generation method as described in claim 1, characterized in that, The step of filtering the crowd to be verified based on the user profile, the crowd gathering event information, and the event processing model to obtain the actual crowd includes: Obtain the user location of each user in the aggregated population to be verified and the detection time corresponding to the user location; Extract event location information and event time information from the crowd gathering event information; The actual cluster of people is obtained by filtering the population to be verified based on the user location, the detection time corresponding to the user location, the event location information, the event time information, the user profile, and the event processing model.

5. The user event tag generation method as described in any one of claims 1-4, characterized in that, After the step of generating event tags for each user in the actual crowd based on the crowd gathering event information, the user event tag generation method further includes: Upon receiving an event tag query request, the event tag query request is parsed to obtain the event number and user number; The target cluster event is determined based on the event number and the user number, and the event information of the target cluster event is obtained.

6. The user event tag generation method as described in any one of claims 1-4, characterized in that, After the step of generating event tags for each user in the actual crowd based on the crowd gathering event information, the user event tag generation method further includes: Obtain business requirement information and generate requirement tags to be combined based on the business requirement information; User marketing tags are generated based on the demand tags to be combined and the event tags, and the user marketing tags are sent to the preset marketing terminal.

7. A user event tag generation device, characterized in that, The user event tag generation device includes: a memory, a processor, and a user event tag generation program stored in the memory and executable on the processor. When the user event tag generation program is executed by the processor, it implements the steps of the user event tag generation method as described in any one of claims 1 to 6.

8. A storage medium, characterized in that, The storage medium stores a user event tag generation program, which, when executed by a processor, implements the steps of the user event tag generation method as described in any one of claims 1 to 6.

9. A user event tag generation device, characterized in that, The user event tag generation device includes: an acquisition module, a filtering module, and a generation module; The acquisition module is used to acquire information on crowd gathering events and determine the crowd to be verified based on the crowd gathering event information, wherein the crowd gathering event information includes the name of the crowd gathering event, the location of the crowd gathering, and the time of the crowd gathering. The acquisition module is also used to acquire user profiles of each user in the population to be verified, wherein the user profiles include user information, communication behavior and internet access behavior; The filtering module is used to filter the crowd to be verified based on the user profile and the crowd gathering event information to obtain the actual crowd. The generation module is used to generate event tags for each user in the actual crowd based on the crowd gathering event information; The filtering module is further configured to: determine the event name of the crowd gathering event based on the crowd gathering event information; classify the crowd gathering event according to the event name to obtain the event category corresponding to the crowd gathering event, wherein the event category includes motion pattern events and fixed pattern events; search for the event processing model corresponding to the motion pattern event or the fixed pattern event in a preset model library; and filter the crowd to be verified based on the user profile, the crowd gathering event information, and the event processing model to obtain the actual crowd.

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