A data processing method and device, electronic equipment and storage medium

Abstract

The application provides a data processing method and device, electronic equipment and storage medium. According to the historical search behavior data of a target user on a network platform, the historical interaction behavior data of the target user on the network platform and the historical operation behavior data of an associated user associated with the target user on the network platform, a current search portrait of the target user can be accurately constructed. According to the more accurate search portrait of the target user, the target user is more likely to use the search recommendation word in the current search scene, thereby improving the possibility that the search recommendation word recommended to the target user is used by the target user in the current search scene, improving the conversion rate of the search recommendation word recommended to the target user, and further improving the exposure rate of the service (provided by the network platform) corresponding to the search recommendation word recommended to the user, and further improving the user experience.

Description

Technical Field

[0001] This invention relates to the field of computer technology, and in particular to a data processing method, apparatus, electronic device, and storage medium. Background Technology

[0002] With the continuous development of technology, internet-based search services have become increasingly mature, and more and more users are searching for the information they want to see online.

[0003] When users search for information on the web, they can enter search terms in the input boxes displayed on the webpage to search for information online using those terms.

[0004] Sometimes, to guide or help users search for information online, you can recommend search terms so that users can quickly find the information they want to view based on the recommended search terms. This can reduce the user's search costs and improve the accuracy of the search.

[0005] In one approach, the most frequently used search terms in historical search scenarios can be statistically analyzed in advance. Then, when each user needs to search for information online, these frequently used search terms from historical search scenarios can be recommended to them.

[0006] However, the inventors discovered that some users may not be interested in search terms that have been frequently used in their historical search scenarios. In such cases, the accuracy of the recommended search terms for these users is low, resulting in low conversion rates and potentially reducing the user experience. Summary of the Invention

[0007] This application discloses a data processing method, apparatus, electronic device, and storage medium.

[0008] In a first aspect, this application discloses a data processing method applied to a terminal, the method comprising:

[0009] In a scenario where a target user uses the terminal to search for resources on a network platform, the system acquires the target user's historical search behavior data on the network platform, the target user's historical interaction behavior data on the network platform, and the historical manipulation behavior data of associated users of the target user on the network platform.

[0010] At least one search recommendation term is obtained based on the historical search behavior data, the historical interaction behavior data, and the historical control behavior data;

[0011] The at least one search recommendation term is displayed on the screen of the terminal.

[0012] In one optional implementation, obtaining the target user's historical search behavior data on the network platform includes:

[0013] Obtain the search terms used by the target user in historical search scenarios and the number of times each search term was used;

[0014] Historical search behavior data is obtained based on the search terms used and the number of times each search term was used.

[0015] In one optional implementation, obtaining historical search behavior data based on the search terms used and the number of times each search term was used includes:

[0016] In descending order of frequency of use, at least one search term is selected from the used search terms and used as the historical search behavior data.

[0017] In an optional implementation, obtaining the search terms used by the target user in historical search scenarios and the number of times each search term was used includes:

[0018] In the first correspondence between the search terms used by the target user in historical search scenarios and the number of times the search terms were used, each search term used in historical search scenarios and the number of times each search term was used were obtained.

[0019] In an optional implementation, the method further includes:

[0020] Obtain a keyword set, which includes multiple keywords determined based on the services provided by the network platform;

[0021] Whenever the target user uses a search term in a historical search scenario, determine whether the search term is located in the keyword set;

[0022] If the search term is located in the keyword set, the search term is searched in the first correspondence.

[0023] If a search term is found in the first correspondence, the usage count corresponding to the search term is increased in the first correspondence.

[0024] If the search term is not found in the first correspondence, an initial value for the number of uses is set, and the search term and the initial value for the number of uses are combined into a corresponding table entry and stored in the first correspondence.

[0025] In one optional implementation, obtaining the target user's historical interaction behavior data on the network platform includes:

[0026] Obtain the interaction words used by the target user in historical interaction scenarios and the number of times each interaction word was used;

[0027] Historical interaction behavior data is obtained based on the interaction words used and the number of times each interaction word was used.

[0028] In one optional implementation, obtaining historical interaction behavior data based on used interaction words and the number of times each interaction word has been used includes:

[0029] In descending order of usage frequency, at least one interactive word is selected from the used interactive words and used as the historical interactive behavior data.

[0030] In an optional implementation, obtaining the interaction words used by the target user in historical interaction scenarios and the number of times each interaction word was used includes:

[0031] In the second correspondence between the interaction words used by the target user in the historical interaction scenario and the number of times the interaction words were used, each interaction word used in the historical interaction scenario and the number of times each interaction word was used were obtained.

[0032] In an optional implementation, the method further includes:

[0033] Obtain a keyword set, which includes multiple keywords determined based on the services provided by the network platform;

[0034] Whenever the target user uses an interaction word in a historical interaction scenario, determine whether the interaction word is located in the keyword set;

[0035] If the interaction word is located in the keyword set, the interaction word is searched in the second correspondence.

[0036] If the interaction word is found in the second correspondence, the usage count corresponding to the interaction word is increased in the first correspondence.

[0037] If the interaction word is not found in the second correspondence, an initial value for the number of uses is set, and the interaction word and the initial value for the number of uses are combined into a corresponding table entry and stored in the second correspondence.

[0038] In an optional implementation, obtaining the historical operation behavior data of the associated users of the target user on the network platform includes:

[0039] The system obtains the control words used by the associated user in historical control scenarios and the number of times each control word was used; the historical control scenarios include at least historical search scenarios and / or historical interaction scenarios, and the control words include at least search terms and / or interaction terms.

[0040] Historical manipulation behavior data is obtained based on the manipulation words used and the number of times each manipulation word was used.

[0041] In one optional implementation, obtaining historical manipulation behavior data based on the manipulated words used and the number of times each manipulated word was used includes:

[0042] In descending order of usage frequency, at least one control word is selected from the used control words and used as the historical control behavior data.

[0043] In one optional implementation, obtaining the control words used by the associated user in historical control scenarios and the number of times each control word was used includes:

[0044] In the third correspondence between the control words used by the associated user in historical control scenarios and the number of times the control words were used, each control word used in the historical control scenarios and the number of times each control word was used were obtained.

[0045] In an optional implementation, the method further includes:

[0046] For any associated user associated with the target user, obtain the first correspondence relationship and the second correspondence relationship corresponding to the associated user. The first correspondence relationship corresponding to the associated user includes the correspondence relationship between the search terms used by the associated user in historical search scenarios and the number of times the search terms were used. The second correspondence relationship corresponding to the associated user includes the correspondence relationship between the interaction terms used by the associated user in historical interaction scenarios and the number of times the interaction terms were used.

[0047] For any word in the first and second correspondence relationships, the word is searched in the third correspondence relationship between the control words used by the associated user in historical control scenarios and the number of times the control words were used.

[0048] If the word is found in the third correspondence, the usage count corresponding to the word is added to the third correspondence based on the usage count of the word in the first correspondence and / or the usage count of the word in the second correspondence;

[0049] If the word is not found in the third correspondence, an initial value for the number of uses is set, and the word and the initial value for the number of uses are combined into a corresponding entry and stored in the third correspondence.

[0050] In one optional implementation, the historical search behavior data includes: the search terms used by the target user in historical search scenarios and the number of times each search term was used; the historical interaction behavior data includes: the interaction terms used by the target user in historical interaction scenarios and the number of times each interaction term was used; the historical manipulation behavior data includes: the manipulation terms used by the associated user in historical manipulation scenarios and the number of times each manipulation term was used; the historical manipulation scenarios include at least historical search scenarios and / or historical interaction scenarios, and the manipulation terms include at least search terms and / or interaction terms;

[0051] The step of obtaining at least one search recommendation term based on the historical search behavior data, the historical interaction behavior data, and the historical control behavior data includes:

[0052] For any one of the search term, the interaction term, and the control term, the recommendation score of the term is obtained based on the number of times the target user uses the term in historical search scenarios, the number of times the target user uses the term in historical interaction scenarios, and the number of times the associated user uses the term in historical control scenarios.

[0053] Based on the recommendation scores of each word among the search term, interaction term, and manipulation term, from highest to lowest, at least one word is selected as the search recommendation term.

[0054] In an optional implementation, obtaining the recommendation score for the word based on the number of times the target user uses the word in historical search scenarios, the number of times the target user uses the word in historical interaction scenarios, and the number of times the associated user uses the word in historical operation scenarios includes:

[0055] Based on the number of times the target user used the word in historical search scenarios, the number of times the target user used the word in historical interaction scenarios, and the number of times the associated user used the word in historical operation scenarios, the recommendation score of the word is calculated according to the following formula:

[0056] Score = w1*H + w2*C + w3*S;

[0057] In the above formula, Score is the recommended score of the word, w1 is the first preset coefficient, w2 is the second preset coefficient, w3 is the third preset coefficient, H is the number of times the target user uses the word in historical search scenarios, C is the number of times the target user uses the word in historical interaction scenarios, and S is the number of times the associated user uses the word in historical control scenarios.

[0058] Secondly, this application discloses a data processing apparatus for use in a terminal, the apparatus comprising:

[0059] The first acquisition module is used to acquire the target user's historical search behavior data on the network platform in the scenario where the target user uses the terminal to search for resources on the network platform; the second acquisition module is used to acquire the target user's historical interaction behavior data on the network platform; and the third acquisition module is used to acquire the target user's historical operation behavior data on the network platform.

[0060] The fourth acquisition module is used to acquire at least one search recommendation term based on the historical search behavior data, the historical interaction behavior data, and the historical operation behavior data;

[0061] A display module is used to display the at least one search recommendation term on the screen of the terminal.

[0062] In an optional implementation, the first acquisition module includes:

[0063] The first acquisition unit is used to acquire the search terms used by the target user in historical search scenarios and the number of times each search term was used.

[0064] The second acquisition unit is used to acquire historical search behavior data based on the search terms used and the number of times each search term was used.

[0065] In one optional implementation, the second acquisition unit includes:

[0066] The first selection subunit is used to select at least one search term from the search terms used in descending order of usage frequency, and use it as the historical search behavior data.

[0067] In one optional implementation, the first acquisition unit includes:

[0068] The first acquisition subunit is used to acquire, from the first correspondence between the search terms used by the target user in the historical search scenario and the number of times each search term was used, each search term used in the historical search scenario and the number of times each search term was used.

[0069] In an optional implementation, the first acquisition unit further includes:

[0070] The second acquisition subunit is used to acquire a keyword set, which includes multiple keywords, and the multiple keywords are determined based on the services provided by the network platform;

[0071] The first determining subunit is used to determine whether a search term is located in the keyword set whenever the target user uses a search term in a historical search scenario.

[0072] The first search subunit is used to search for the search term in the first correspondence when the search term is located in the keyword set;

[0073] The first addition subunit is used to add the usage count corresponding to the search term in the first correspondence when the search term is found in the first correspondence.

[0074] The first storage subunit is used to set an initial value for the number of uses when the search term is not found in the first correspondence, to form a corresponding table entry with the search term and the initial value for the number of uses, and to store it in the first correspondence.

[0075] In one optional implementation, the second acquisition module includes:

[0076] The third acquisition unit is used to acquire the interaction words used by the target user in historical interaction scenarios and the number of times each interaction word was used.

[0077] The fourth acquisition unit is used to acquire historical interaction behavior data based on the interaction words used and the number of times each interaction word was used.

[0078] In one optional implementation, the fourth root acquisition unit includes:

[0079] The second selection subunit is used to select at least one interaction word from the interaction words that have been used, in descending order of usage frequency, and use it as the historical interaction behavior data.

[0080] In one optional implementation, the third acquisition unit includes:

[0081] The third acquisition subunit is used to acquire, from the second correspondence between the interaction words used by the target user in the historical interaction scenario and the number of times the interaction words are used, each interaction word used in the historical interaction scenario and the number of times each interaction word is used.

[0082] In an optional implementation, the third acquisition unit further includes:

[0083] The fourth acquisition subunit is used to acquire a keyword set, which includes multiple keywords, and the multiple keywords are determined based on the services provided by the network platform;

[0084] The second determining subunit is used to determine whether an interaction word is located in the keyword set whenever the target user uses an interaction word in a historical interaction scenario.

[0085] The second search subunit is used to search for the interaction word in the second correspondence when the interaction word is located in the keyword set;

[0086] The second additional subunit is used to add the usage count corresponding to the interaction word in the first correspondence when the interaction word is found in the second correspondence;

[0087] The second storage subunit is used to set an initial value for the number of uses when the interaction word is not found in the second correspondence, to form a corresponding table entry with the interaction word and the initial value for the number of uses, and to store it in the second correspondence.

[0088] In one optional implementation, the third acquisition module includes:

[0089] The fifth acquisition unit is used to acquire the control words used by the associated user in historical control scenarios and the number of times each control word was used; the historical control scenarios include at least historical search scenarios and / or historical interaction scenarios, and the control words include at least search terms and / or interaction terms;

[0090] The sixth acquisition unit is used to acquire historical control behavior data based on the control words used and the number of times each control word was used.

[0091] In an optional implementation, the sixth acquisition unit includes:

[0092] The third selection subunit is used to select at least one control word from the control words that have been used, in descending order of usage frequency, and use it as the historical control behavior data.

[0093] In one optional implementation, the fifth acquisition unit includes:

[0094] The fifth acquisition subunit is used to acquire, from the third correspondence between the control words used by the associated user in the historical control scenario and the number of times the control words are used, each control word used in the historical control scenario and the number of times each control word is used.

[0095] In an optional implementation, the fifth acquisition unit further includes:

[0096] The sixth acquisition subunit is used to acquire, for any associated user associated with the target user, a first correspondence relationship and a second correspondence relationship corresponding to the associated user. The first correspondence relationship corresponding to the associated user includes the correspondence between the search terms used by the associated user in historical search scenarios and the number of times the search terms were used. The second correspondence relationship corresponding to the associated user includes the correspondence between the interaction terms used by the associated user in historical interaction scenarios and the number of times the interaction terms were used.

[0097] The third search subunit is used to search for any word in the first correspondence relationship and the second correspondence relationship in the third correspondence relationship between the control words used by the associated user in historical control scenarios and the number of times the control words were used.

[0098] The third subunit is used to, when the word is found in the third correspondence, add the usage count corresponding to the word in the third correspondence according to the usage count of the word in the first correspondence and / or the usage count of the word in the second correspondence;

[0099] The third storage subunit is used to set an initial value for the number of uses when the word is not found in the third correspondence, form a corresponding table entry with the word and the initial value for the number of uses, and store it in the third correspondence.

[0100] In one optional implementation, the historical search behavior data includes: the search terms used by the target user in historical search scenarios and the number of times each search term was used; the historical interaction behavior data includes: the interaction terms used by the target user in historical interaction scenarios and the number of times each interaction term was used; the historical manipulation behavior data includes: the manipulation terms used by the associated user in historical manipulation scenarios and the number of times each manipulation term was used; the historical manipulation scenarios include at least historical search scenarios and / or historical interaction scenarios, and the manipulation terms include at least search terms and / or interaction terms;

[0101] The fourth acquisition module includes:

[0102] The seventh acquisition unit is used to acquire a recommendation score for any one of the search terms, interaction terms, and control terms, based on the number of times the target user uses the term in historical search scenarios, the number of times the target user uses the term in historical interaction scenarios, and the number of times the associated user uses the term in historical control scenarios.

[0103] The selection unit is used to select at least one word from the search term, the interaction term, and the control term as a search recommendation term, according to the recommendation scores of each word in the search term, the interaction term, and the control term in descending order.

[0104] In an optional implementation, the seventh acquisition unit is specifically used to: calculate the recommendation score of the word according to the following formula based on the number of times the target user uses the word in historical search scenarios, the number of times the target user uses the word in historical interaction scenarios, and the number of times the associated user uses the word in historical operation scenarios:

[0105] Score = w1*H + w2*C + w3*S;

[0106] In the above formula, Score is the recommended score of the word, w1 is the first preset coefficient, w2 is the second preset coefficient, w3 is the third preset coefficient, H is the number of times the target user uses the word in historical search scenarios, C is the number of times the target user uses the word in historical interaction scenarios, and S is the number of times the associated user uses the word in historical control scenarios.

[0107] Thirdly, this application discloses an electronic device comprising:

[0108] processor;

[0109] Memory used to store processor-executable instructions;

[0110] The processor is configured to perform the data processing method as described in the first aspect.

[0111] Fourthly, this application discloses a non-transitory computer-readable storage medium in which, when instructions in the storage medium are executed by a processor of an electronic device, enable the electronic device to perform the data processing method as described in the first aspect.

[0112] Fifthly, this application discloses a computer program product in which, when the instructions in the computer program product are executed by a processor of an electronic device, the electronic device is enabled to perform the data processing method as described in the first aspect.

[0113] The technical solution provided in this application may include the following beneficial effects:

[0114] In this application, in a scenario where a target user searches for resources on a network platform using a terminal, the system acquires the target user's historical search behavior data, historical interaction behavior data, and historical control behavior data of associated users on the network platform. Based on the historical search behavior data, historical interaction behavior data, and historical control behavior data, at least one search recommendation term is obtained. The terminal's screen displays at least one search recommendation term.

[0115] Among them, the target user's current search profile can be accurately constructed based on the target user's historical search behavior data on the online platform, the target user's historical interaction behavior data on the online platform, and the historical manipulation behavior data of the target user's associated users on the online platform.

[0116] For example, by analyzing a target user's historical search behavior data on an online platform, their direct search needs can be identified. By analyzing a target user's historical interaction behavior data on an online platform, their indirect search needs can be identified. In addition, related users often have the same or similar needs. Therefore, by analyzing the historical manipulation behavior data of related users on an online platform, the target user's potential search needs can be mined. Thus, based on direct search needs, indirect search needs, and potential search needs, a more accurate current search profile of the target user can be constructed.

[0117] By creating a more precise search profile of the target user, we can identify the search terms that the target user is more likely to use in the current search scenario. This increases the likelihood that the recommended search terms will be used by the target user in the current search scenario, thereby increasing the conversion rate of the recommended search terms. In turn, it can increase the exposure of the services (provided by the online platform) corresponding to the recommended search terms, and ultimately improve the user experience. Attached Figure Description

[0118] Figure 1 This is a flowchart of the steps of a data processing method according to this application.

[0119] Figure 2 This is a structural block diagram of a data processing device according to this application.

[0120] Figure 3This is a block diagram of an electronic device according to this application.

[0121] Figure 4 This is a block diagram of an electronic device according to this application. Detailed Implementation

[0122] The technical solutions of the embodiments of the present invention will be clearly and completely described below with reference to the accompanying drawings. Obviously, the described embodiments are only some, not all, of the embodiments of the present invention. Based on the embodiments of the present invention, all other embodiments obtained by those skilled in the art without creative effort are within the scope of protection of the present invention.

[0123] Reference Figure 1 The diagram illustrates a flowchart of a data processing method according to this application, applied to a terminal. The method may specifically include the following steps:

[0124] In step S101, in the scenario where the target user uses a terminal to search for resources on the network platform, the target user's historical search behavior data on the network platform, the target user's historical interaction behavior data on the network platform, and the target user's associated historical manipulation behavior data on the network platform are obtained.

[0125] In this application, when a webpage is displayed on the terminal screen and the webpage has a search box, the user clicks the search box and enters a scenario of searching for resources on the network platform. The user is in a scenario of searching for resources on the network platform while entering search terms in the search box.

[0126] In a scenario where a target user uses a terminal to search for resources on a network platform, the system can obtain the target user's historical search behavior data on the network platform, the target user's historical interaction behavior data on the network platform, and the historical manipulation behavior data of associated users of the target user on the network platform, and then execute step S102.

[0127] In one embodiment, obtaining historical search behavior data of a target user on a web platform can be achieved through the following process:

[0128] 11) Obtain the search terms used by the target user in historical search scenarios and the number of times each search term was used.

[0129] A keyword set can be obtained in advance, containing multiple keywords determined based on the services provided by the online platform. For any service offered by the online platform, the platform can automatically generate at least one keyword describing the service's theme based on its characteristics or attributes. Alternatively, the platform's staff can manually generate at least one keyword describing the service's theme based on its characteristics or attributes. The same process is repeated for each other service offered by the platform, resulting in at least one keyword for each service. All these keywords can then be combined into a keyword set.

[0130] Whenever a target user uses a search term in a historical search scenario (for example, when a target user enters search text in the search box on a web platform's page and requests search resources from the platform based on that search text, the search text can be analyzed to obtain keywords describing the search topic, which are then used as search terms. These keywords may be a part or all of the words in the search text), it can be determined whether that search term is located in the keyword set. If a search term is not located in the keyword set, it indicates that the search term is not closely related to the services provided by the web platform, and therefore, it does not need to be recorded.

[0131] When a search term is located in the keyword set, it indicates that the search term is related to at least one service provided by the network platform. Thus, the search term can be found in the first correspondence between the search terms used by the target user in historical search scenarios and the number of times the search term was used.

[0132] If a search term is found in the first correspondence between the search terms used by the target user in historical search scenarios and the number of times the search term is used, the number of times the search term is used is increased in the first correspondence. For example, in the first correspondence between the search terms used by the target user in historical search scenarios and the number of times the search term is used, the number of times the search term is used is increased by 1.

[0133] If a search term is not found in the first correspondence between the search terms used by the target user in historical search scenarios and the number of times the search term was used, an initial value for the number of times it was used is set. In one example, the number of times it was used can be 1, etc. Then, the search term and the initial value for the number of times it was used can be combined into a corresponding table entry and stored in the first correspondence.

[0134] Thus, in step 11), the first correspondence between the search terms used by the target user in the historical search scenario and the number of times each search term was used can be obtained from the first correspondence between the search terms used by the target user in the historical search scenario and the number of times each search term was used.

[0135] 12) Obtain historical search behavior data based on the search terms used and the number of times each search term was used.

[0136] In one embodiment of this application, at least one search term can be selected from the search terms used in descending order of frequency of use and used as historical search behavior data.

[0137] In one embodiment, obtaining historical interaction data of a target user on a network platform can be achieved through the following process:

[0138] 21) Obtain the interaction words used by the target user in historical interaction scenarios and the number of times each interaction word was used.

[0139] A keyword set can be obtained in advance, containing multiple keywords determined based on the services provided by the online platform. For any service offered by the online platform, the platform can automatically generate at least one keyword describing the service's theme based on its characteristics or attributes. Alternatively, the platform's staff can manually generate at least one keyword describing the service's theme based on its characteristics or attributes. The same process is repeated for each other service offered by the platform, resulting in at least one keyword for each service. All these keywords can then be combined into a keyword set.

[0140] Whenever a target user uses an interaction word in a historical interaction scenario (for example, a target user posts a comment on a resource displayed on a page provided by the online platform, or posts text for a wide audience to view on a page provided by the online platform (such as a post), the posted text can be analyzed to obtain keywords describing the topic of the posted text, and these keywords can be used as interaction words. These keywords may be a part or all of the words in the posted text), it can be determined whether that interaction word is located in the keyword set. If an interaction word is not located in the keyword set, it indicates that the interaction word is not closely related to the services provided by the online platform, and therefore, it can be left unrecorded.

[0141] When an interaction word is located in the keyword set, it indicates that the interaction word is related to at least one service provided by the network platform. Thus, the interaction word can be found in the second correspondence between the interaction words used by the target user in historical interaction scenarios and the number of times the interaction word was used.

[0142] If an interaction word is found in the second correspondence between the interaction words used by the target user in historical interaction scenarios and the number of times the interaction word is used, the number of times the interaction word is used is increased in the second correspondence. For example, in the second correspondence between the interaction words used by the target user in historical interaction scenarios and the number of times the interaction word is used, the number of times the interaction word is used is increased by 1.

[0143] If an interaction word is not found in the second correspondence between the interaction words used by the target user in historical interaction scenarios and the number of times the interaction word has been used, an initial value for the number of times the interaction word has been set. In one example, the number of times the interaction word can be 1, etc. Then, the interaction word and the initial value for the number of times the interaction word has been combined into a corresponding table entry and stored in the second correspondence.

[0144] Thus, in step 21), the second correspondence between the interaction words used by the target user in the historical interaction scenario and the number of times the interaction words were used can be obtained, which includes each interaction word used in the historical interaction scenario and the number of times each interaction word was used.

[0145] 22) Obtain historical interaction behavior data based on the interaction words used and the number of times each interaction word was used.

[0146] In one embodiment of this application, at least one interactive word can be selected from the interactive words that have been used, in descending order of usage frequency, and used as historical interactive behavior data.

[0147] In one embodiment, obtaining historical data on the operational behavior of associated users of the target user on the network platform includes:

[0148] 31) Obtain the control terms used by the associated user in historical control scenarios and the number of times each control term was used. Historical control scenarios include at least historical search scenarios and / or historical interaction scenarios, and control terms include at least search terms and / or interaction terms.

[0149] It is possible to identify associated users of the target user. Associated users can include the target user's friends, such as users who have a friend relationship with the target user on the online platform, or users in the friend list of the target user's registered account on the online platform. The target user can have one or more associated users.

[0150] For any associated user of the target user, a first correspondence and a second correspondence can be obtained. The first correspondence includes the correspondence between the search terms used by the associated user in historical search scenarios and the number of times those terms were used. The second correspondence includes the correspondence between the interaction terms used by the associated user in historical interaction scenarios and the number of times those interaction terms were used. The methods for generating these first and second correspondences can be found in the aforementioned embodiments regarding the first correspondence between the search terms used by the target user in historical search scenarios and the second correspondence between the interaction terms used by the target user in historical interaction scenarios and the number of times those interaction terms were used, and will not be detailed here.

[0151] For any word in the first and second correspondences of the associated user, search for that word in the third correspondence between the control words used by the associated user in historical control scenarios and the number of times the control words were used.

[0152] If the word is found in the third correspondence between the control words used by the associated user in historical control scenarios and the number of times the control words are used, the number of times the word is used is added to the third correspondence between the control words used by the associated user in historical control scenarios and the number of times the control words are used, based on the number of times the word is used in the first correspondence and / or the number of times the word is used in the second correspondence.

[0153] If the word is not found in the third correspondence between the control words used by the user in the historical control scenarios and the number of times the control words are used, an initial value for the number of times the words are used is set. In one example, the number of times the words are used can be 1, etc. Then the word and the initial value of the number of times the words are used can be combined into a corresponding table entry and stored in the third correspondence.

[0154] Thus, in step 31), the third correspondence between the control words used by the associated user in the historical control scenario and the number of times the control words were used can be obtained, which includes each control word used in the historical control scenario and the number of times each control word was used.

[0155] Additionally, whenever an associated user uses a manipulation term in a historical manipulation scenario (historical manipulation scenarios include at least historical search scenarios and / or historical interaction scenarios, and manipulation terms include at least search terms and / or interaction terms), the number of manipulations corresponding to that manipulation term can be updated in the third correspondence between the manipulation terms used by the associated users in historical manipulation scenarios and the number of times those manipulation terms were used. The specific update method can be found in the foregoing description and will not be detailed here.

[0156] 32) Obtain historical manipulation behavior data based on the manipulation words used and the number of times each manipulation word was used.

[0157] In one embodiment of this application, at least one control word can be selected from the control words that have been used, in descending order of the number of times they have been used, and used as historical control behavior data.

[0158] In step S102, at least one search recommendation term is obtained based on historical search behavior data, historical interaction behavior data, and historical manipulation behavior data.

[0159] In this application, historical search behavior data includes: search terms used by the target user in historical search scenarios and the frequency of use of each search term. Historical interaction behavior data includes: interaction terms used by the target user in historical interaction scenarios and the frequency of use of each interaction term. Historical manipulation behavior data includes: manipulation terms used by the associated user in historical manipulation scenarios and the frequency of use of each manipulation term. Historical manipulation scenarios include at least historical search scenarios and / or historical interaction scenarios, and manipulation terms include at least search terms and / or interaction terms.

[0160] Therefore, this step can be achieved through the following process:

[0161] 1021. For any one of the search terms, interaction terms, and manipulation terms, obtain the recommendation score for that term based on the number of times the target user used the term in historical search scenarios, the number of times the target user used the term in historical interaction scenarios, and the number of times the associated user used the term in historical manipulation scenarios.

[0162] Alternatively, duplicates can be removed from the search terms used by the target user in historical search scenarios, the interaction terms used by the target user in historical interaction scenarios, and the control terms used by related users in historical control scenarios. Then, for any one of these duplicate terms, a recommendation score can be obtained based on the number of times the target user used the term in historical search scenarios, the number of times the target user used the term in historical interaction scenarios, and the number of times related users used the term in historical control scenarios.

[0163] The recommendation score for a keyword can be calculated using the following formula, based on the frequency of the keyword's usage by the target user in historical search scenarios, the frequency of the keyword's usage by the target user in historical interaction scenarios, and the frequency of the keyword's usage by related users in historical manipulation scenarios:

[0164] Score = w1*H + w2*C + w3*S.

[0165] In the above formula, Score is the recommended score of the word, w1 is the first preset coefficient, w2 is the second preset coefficient, w3 is the third preset coefficient, H is the number of times the target user uses the word in historical search scenarios, C is the number of times the target user uses the word in historical interaction scenarios, and S is the number of times the associated user uses the word in historical control scenarios.

[0166] The first preset coefficient w1, the second preset coefficient w2, and the third preset coefficient w3 can be determined according to the actual situation. This application does not limit the specific values ​​of the first preset coefficient w1, the second preset coefficient w2, and the third preset coefficient w3.

[0167] In one example, the sum of the first preset coefficient w1, the second preset coefficient w2, and the third preset coefficient w3 can be equal to a specific value, such as 1, 1.5, or 2, etc., which is not limited in this application.

[0168] The first preset coefficient w1 can be greater than or equal to 0 and less than or equal to a specific value; the second preset coefficient w2 can be greater than or equal to 0 and less than or equal to a specific value; the third preset coefficient w3 can be greater than or equal to 0 and less than or equal to a specific value, and so on.

[0169] 1021. Based on the recommendation scores of each word in the search term, interaction term, and manipulation term in descending order, select at least one word from the search term, interaction term, and manipulation term as the search recommendation term.

[0170] In step S103, at least one search recommendation term is displayed on the terminal screen.

[0171] In one embodiment of this application, at least one search recommendation term may be displayed near or around the search box on the webpage displayed on the screen, for example, at least one search recommendation term may be displayed below the search box.

[0172] In this application, in a scenario where a target user searches for resources on a network platform using a terminal, the system acquires the target user's historical search behavior data, historical interaction behavior data, and historical control behavior data of associated users on the network platform. Based on the historical search behavior data, historical interaction behavior data, and historical control behavior data, at least one search recommendation term is obtained. The terminal's screen displays at least one search recommendation term.

[0173] Among them, the target user's current search profile can be accurately constructed based on the target user's historical search behavior data on the online platform, the target user's historical interaction behavior data on the online platform, and the historical manipulation behavior data of the target user's associated users on the online platform.

[0174] For example, by analyzing a target user's historical search behavior data on an online platform, their direct search needs can be identified. By analyzing a target user's historical interaction behavior data on an online platform, their indirect search needs can be identified. In addition, related users often have the same or similar needs. Therefore, by analyzing the historical manipulation behavior data of related users on an online platform, the target user's potential search needs can be mined. Thus, based on direct search needs, indirect search needs, and potential search needs, a more accurate current search profile of the target user can be constructed.

[0175] By creating a more precise search profile of the target user, we can identify the search terms that the target user is more likely to use in the current search scenario. This increases the likelihood that the recommended search terms will be used by the target user in the current search scenario, thereby increasing the conversion rate of the recommended search terms. In turn, it can increase the exposure of the services (provided by the online platform) corresponding to the recommended search terms, and ultimately improve the user experience.

[0176] It should be noted that, for the sake of simplicity, the method embodiments are all described as a series of actions. However, those skilled in the art should understand that this application is not limited to the described order of actions, because according to this application, some steps can be performed in other orders or simultaneously. Secondly, those skilled in the art should also understand that the embodiments described in the specification are all optional embodiments, and the actions involved are not necessarily required by this application.

[0177] Reference Figure 2 The diagram shows a structural block diagram of a data processing apparatus according to this application, which is applied to a terminal. The apparatus may specifically include the following modules:

[0178] The first acquisition module 11 is used to acquire the target user's historical search behavior data on the network platform in the scenario where the target user uses the terminal to search for resources on the network platform; the second acquisition module 12 is used to acquire the target user's historical interaction behavior data on the network platform; and the third acquisition module 13 is used to acquire the historical operation behavior data of the associated users of the target user on the network platform.

[0179] The fourth acquisition module 14 is used to acquire at least one search recommendation term based on the historical search behavior data, the historical interaction behavior data, and the historical operation behavior data;

[0180] Display module 15 is used to display the at least one search recommendation term on the screen of the terminal.

[0181] In an optional implementation, the first acquisition module includes:

[0182] The first acquisition unit is used to acquire the search terms used by the target user in historical search scenarios and the number of times each search term was used.

[0183] The second acquisition unit is used to acquire historical search behavior data based on the search terms used and the number of times each search term was used.

[0184] In one optional implementation, the second acquisition unit includes:

[0185] The first selection subunit is used to select at least one search term from the search terms used in descending order of usage frequency, and use it as the historical search behavior data.

[0186] In one optional implementation, the first acquisition unit includes:

[0187] The first acquisition subunit is used to acquire, from the first correspondence between the search terms used by the target user in the historical search scenario and the number of times each search term was used, each search term used in the historical search scenario and the number of times each search term was used.

[0188] In an optional implementation, the first acquisition unit further includes:

[0189] The second acquisition subunit is used to acquire a keyword set, which includes multiple keywords, and the multiple keywords are determined based on the services provided by the network platform;

[0190] The first determining subunit is used to determine whether a search term is located in the keyword set whenever the target user uses a search term in a historical search scenario.

[0191] The first search subunit is used to search for the search term in the first correspondence when the search term is located in the keyword set;

[0192] The first addition subunit is used to add the usage count corresponding to the search term in the first correspondence when the search term is found in the first correspondence.

[0193] The first storage subunit is used to set an initial value for the number of uses when the search term is not found in the first correspondence, to form a corresponding table entry with the search term and the initial value for the number of uses, and to store it in the first correspondence.

[0194] In one optional implementation, the second acquisition module includes:

[0195] The third acquisition unit is used to acquire the interaction words used by the target user in historical interaction scenarios and the number of times each interaction word was used.

[0196] The fourth acquisition unit is used to acquire historical interaction behavior data based on the interaction words used and the number of times each interaction word was used.

[0197] In one optional implementation, the fourth root acquisition unit includes:

[0198] The second selection subunit is used to select at least one interaction word from the interaction words that have been used, in descending order of usage frequency, and use it as the historical interaction behavior data.

[0199] In one optional implementation, the third acquisition unit includes:

[0200] The third acquisition subunit is used to acquire, from the second correspondence between the interaction words used by the target user in the historical interaction scenario and the number of times the interaction words are used, each interaction word used in the historical interaction scenario and the number of times each interaction word is used.

[0201] In an optional implementation, the third acquisition unit further includes:

[0202] The fourth acquisition subunit is used to acquire a keyword set, which includes multiple keywords, and the multiple keywords are determined based on the services provided by the network platform;

[0203] The second determining subunit is used to determine whether an interaction word is located in the keyword set whenever the target user uses an interaction word in a historical interaction scenario.

[0204] The second search subunit is used to search for the interaction word in the second correspondence when the interaction word is located in the keyword set;

[0205] The second additional subunit is used to add the usage count corresponding to the interaction word in the first correspondence when the interaction word is found in the second correspondence;

[0206] The second storage subunit is used to set an initial value for the number of uses when the interaction word is not found in the second correspondence, to form a corresponding table entry with the interaction word and the initial value for the number of uses, and to store it in the second correspondence.

[0207] In one optional implementation, the third acquisition module includes:

[0208] The fifth acquisition unit is used to acquire the control words used by the associated user in historical control scenarios and the number of times each control word was used; the historical control scenarios include at least historical search scenarios and / or historical interaction scenarios, and the control words include at least search terms and / or interaction terms;

[0209] The sixth acquisition unit is used to acquire historical control behavior data based on the control words used and the number of times each control word was used.

[0210] In an optional implementation, the sixth acquisition unit includes:

[0211] The third selection subunit is used to select at least one control word from the control words that have been used, in descending order of usage frequency, and use it as the historical control behavior data.

[0212] In one optional implementation, the fifth acquisition unit includes:

[0213] The fifth acquisition subunit is used to acquire, from the third correspondence between the control words used by the associated user in the historical control scenario and the number of times the control words are used, each control word used in the historical control scenario and the number of times each control word is used.

[0214] In an optional implementation, the fifth acquisition unit further includes:

[0215] The sixth acquisition subunit is used to acquire, for any associated user associated with the target user, a first correspondence relationship and a second correspondence relationship corresponding to the associated user. The first correspondence relationship corresponding to the associated user includes the correspondence between the search terms used by the associated user in historical search scenarios and the number of times the search terms were used. The second correspondence relationship corresponding to the associated user includes the correspondence between the interaction terms used by the associated user in historical interaction scenarios and the number of times the interaction terms were used.

[0216] The third search subunit is used to search for any word in the first correspondence relationship and the second correspondence relationship in the third correspondence relationship between the control words used by the associated user in historical control scenarios and the number of times the control words were used.

[0217] The third subunit is used to, when the word is found in the third correspondence, add the usage count corresponding to the word in the third correspondence according to the usage count of the word in the first correspondence and / or the usage count of the word in the second correspondence;

[0218] The third storage subunit is used to set an initial value for the number of uses when the word is not found in the third correspondence, form a corresponding table entry with the word and the initial value for the number of uses, and store it in the third correspondence.

[0219] In one optional implementation, the historical search behavior data includes: the search terms used by the target user in historical search scenarios and the number of times each search term was used; the historical interaction behavior data includes: the interaction terms used by the target user in historical interaction scenarios and the number of times each interaction term was used; the historical manipulation behavior data includes: the manipulation terms used by the associated user in historical manipulation scenarios and the number of times each manipulation term was used; the historical manipulation scenarios include at least historical search scenarios and / or historical interaction scenarios, and the manipulation terms include at least search terms and / or interaction terms;

[0220] The fourth acquisition module includes:

[0221] The seventh acquisition unit is used to acquire a recommendation score for any one of the search terms, interaction terms, and control terms, based on the number of times the target user uses the term in historical search scenarios, the number of times the target user uses the term in historical interaction scenarios, and the number of times the associated user uses the term in historical control scenarios.

[0222] The selection unit is used to select at least one word from the search term, the interaction term, and the control term as a search recommendation term, according to the recommendation scores of each word in the search term, the interaction term, and the control term in descending order.

[0223] In an optional implementation, the seventh acquisition unit is specifically used to: calculate the recommendation score of the word according to the following formula based on the number of times the target user uses the word in historical search scenarios, the number of times the target user uses the word in historical interaction scenarios, and the number of times the associated user uses the word in historical operation scenarios:

[0224] Score = w1*H + w2*C + w3*S;

[0225] In the above formula, Score is the recommended score of the word, w1 is the first preset coefficient, w2 is the second preset coefficient, w3 is the third preset coefficient, H is the number of times the target user uses the word in historical search scenarios, C is the number of times the target user uses the word in historical interaction scenarios, and S is the number of times the associated user uses the word in historical control scenarios.

[0226] In this application, in a scenario where a target user searches for resources on a network platform using a terminal, the system acquires the target user's historical search behavior data, historical interaction behavior data, and historical control behavior data of associated users on the network platform. Based on the historical search behavior data, historical interaction behavior data, and historical control behavior data, at least one search recommendation term is obtained. The terminal's screen displays at least one search recommendation term.

[0227] Among them, the target user's current search profile can be accurately constructed based on the target user's historical search behavior data on the online platform, the target user's historical interaction behavior data on the online platform, and the historical manipulation behavior data of the target user's associated users on the online platform.

[0228] For example, by analyzing a target user's historical search behavior data on an online platform, their direct search needs can be identified. By analyzing a target user's historical interaction behavior data on an online platform, their indirect search needs can be identified. In addition, related users often have the same or similar needs. Therefore, by analyzing the historical manipulation behavior data of related users on an online platform, the target user's potential search needs can be mined. Thus, based on direct search needs, indirect search needs, and potential search needs, a more accurate current search profile of the target user can be constructed.

[0229] By creating a more precise search profile of the target user, we can identify the search terms that the target user is more likely to use in the current search scenario. This increases the likelihood that the recommended search terms will be used by the target user in the current search scenario, thereby increasing the conversion rate of the recommended search terms. In turn, it can increase the exposure of the services (provided by the online platform) corresponding to the recommended search terms, and ultimately improve the user experience.

[0230] As the device embodiment is basically similar to the method embodiment, the description is relatively simple, and relevant parts can be found in the description of the method embodiment.

[0231] Optionally, embodiments of the present invention also provide an electronic device, including: a processor, a memory, and a computer program stored in the memory and executable on the processor. When the computer program is executed by the processor, it implements the various processes of the above-described data processing method embodiments and achieves the same technical effect. To avoid repetition, it will not be described again here.

[0232] This invention also provides a computer-readable storage medium storing a computer program. When the computer program is executed by a processor, it implements the various processes of the above-described data processing method embodiments and achieves the same technical effects. To avoid repetition, it will not be described again here. The computer-readable storage medium may be a read-only memory (ROM), a random access memory (RAM), a magnetic disk, or an optical disk.

[0233] Figure 3 This is a block diagram illustrating an electronic device 800. For example, the electronic device 800 may be a mobile phone, computer, digital broadcasting terminal, messaging device, game console, tablet device, medical device, fitness equipment, personal digital assistant, etc.

[0234] Reference Figure 3 The electronic device 800 may include one or more of the following components: a processing component 802, a memory 804, a power component 806, a multimedia component 808, an audio component 810, an input / output (I / O) interface 812, a sensor component 814, and a communication component 816.

[0235] Processing component 802 typically controls the overall operation of electronic device 800, such as operations associated with display, telephone calls, data communication, camera operation, and recording operations. Processing component 802 may include one or more processors 820 to execute instructions to complete all or part of the steps of the methods described above. Furthermore, processing component 802 may include one or more modules to facilitate interaction between processing component 802 and other components. For example, processing component 802 may include a multimedia module to facilitate interaction between multimedia component 808 and processing component 802.

[0236] Memory 804 is configured to store various types of data to support the operation of device 800. Examples of this data include instructions for any application or method operating on electronic device 800, contact data, phonebook data, messages, images, videos, etc. Memory 804 can be implemented by any type of volatile or non-volatile storage device or a combination thereof, such as static random access memory (SRAM), electrically erasable programmable read-only memory (EEPROM), erasable programmable read-only memory (EPROM), programmable read-only memory (PROM), read-only memory (ROM), magnetic storage, flash memory, magnetic disk, or optical disk.

[0237] Power supply component 806 provides power to various components of electronic device 800. Power supply component 806 may include a power management system, one or more power supplies, and other components associated with generating, managing, and distributing power to electronic device 800.

[0238] Multimedia component 808 includes a screen that provides an output interface between the electronic device 800 and the user. In some embodiments, the screen may include a liquid crystal display (LCD) and a touch panel (TP). If the screen includes a touch panel, the screen may be implemented as a touchscreen to receive input signals from the user. The touch panel includes one or more touch sensors to sense touches, swipes, and gestures on the touch panel. The touch sensors may sense not only the boundaries of the touch or swipe action but also the duration and pressure associated with the touch or swipe operation. In some embodiments, multimedia component 808 includes a front-facing camera and / or a rear-facing camera. When the device 800 is in an operating mode, such as a shooting mode or a video mode, the front-facing camera and / or the rear-facing camera may receive external multimedia data. Each front-facing camera and rear-facing camera may be a fixed optical lens system or have focal length and optical zoom capabilities.

[0239] Audio component 810 is configured to output and / or input audio signals. For example, audio component 810 includes a microphone (MIC) configured to receive external audio signals when electronic device 800 is in an operating mode, such as call mode, recording mode, and voice recognition mode. The received audio signals may be further stored in memory 804 or transmitted via communication component 816. In some embodiments, audio component 810 also includes a speaker for outputting audio signals.

[0240] I / O interface 812 provides an interface between processing component 802 and peripheral interface modules, such as keyboards, click wheels, buttons, etc. These buttons may include, but are not limited to, home buttons, volume buttons, power buttons, and lock buttons.

[0241] Sensor assembly 814 includes one or more sensors for providing state assessments of various aspects of electronic device 800. For example, sensor assembly 814 may detect the on / off state of device 800, the relative positioning of components such as the display and keypad of electronic device 800, changes in position of electronic device 800 or a component of electronic device 800, the presence or absence of user contact with electronic device 800, orientation or acceleration / deceleration of electronic device 800, and temperature changes of electronic device 800. Sensor assembly 814 may include a proximity sensor configured to detect the presence of nearby objects without any physical contact. Sensor assembly 814 may also include a light sensor, such as a CMOS or CCD image sensor, for use in imaging applications. In some embodiments, sensor assembly 814 may also include an accelerometer, gyroscope, magnetometer, pressure sensor, or temperature sensor.

[0242] Communication component 816 is configured to facilitate wired or wireless communication between electronic device 800 and other devices. Electronic device 800 can access wireless networks based on communication standards, such as WiFi, carrier networks (such as 2G, 3G, 4G, or 5G), or combinations thereof. In one exemplary embodiment, communication component 816 receives broadcast signals or broadcast operation information from an external broadcast management system via a broadcast channel. In one exemplary embodiment, communication component 816 also includes a near-field communication (NFC) module to facilitate short-range communication. For example, the NFC module may be implemented based on radio frequency identification (RFID) technology, Infrared Data Association (IrDA) technology, ultra-wideband (UWB) technology, Bluetooth (BT) technology, and other technologies.

[0243] In an exemplary embodiment, the electronic device 800 may be implemented by one or more application-specific integrated circuits (ASICs), digital signal processors (DSPs), digital signal processing devices (DSPDs), programmable logic devices (PLDs), field-programmable gate arrays (FPGAs), controllers, microcontrollers, microprocessors, or other electronic components to perform the methods described above.

[0244] In an exemplary embodiment, a non-transitory computer-readable storage medium including instructions is also provided, such as a memory 804 including instructions, which can be executed by a processor 820 of an electronic device 800 to perform the above-described method. For example, the non-transitory computer-readable storage medium may be a ROM, random access memory (RAM), CD-ROM, magnetic tape, floppy disk, and optical data storage device, etc.

[0245] Figure 4 This is a block diagram of an electronic device 1900 shown in this application. For example, the electronic device 1900 can be provided as a server.

[0246] Reference Figure 4 The electronic device 1900 includes a processing component 1922, which further includes one or more processors, and memory resources represented by memory 1932 for storing instructions, such as application programs, that can be executed by the processing component 1922. The application programs stored in memory 1932 may include one or more modules, each corresponding to a set of instructions. Furthermore, the processing component 1922 is configured to execute instructions to perform the methods described above.

[0247] Electronic device 1900 may also include a power supply component 1926 configured to perform power management of electronic device 1900, a wired or wireless network interface 1950 configured to connect electronic device 1900 to a network, and an input / output (I / O) interface 1958. Electronic device 1900 can operate on an operating system stored in memory 1932, such as Windows Server™, Mac OS X™, Unix™, Linux™, FreeBSD™, or similar.

[0248] 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 apparatus 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 apparatus. 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 apparatus that includes that element.

[0249] 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, in essence, 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 ROM / RAM, magnetic disk, optical disk), and includes several instructions to cause a terminal (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.

[0250] The embodiments of the present invention have been described above with reference to the accompanying drawings. However, the present invention is not limited to the specific embodiments described above. The specific embodiments described above are merely illustrative and not restrictive. Those skilled in the art can make many other forms under the guidance of the present invention without departing from the spirit and scope of the claims, and all of these forms are within the protection scope of the present invention.

[0251] Those skilled in the art will recognize that the units and algorithm steps of the various examples described in conjunction with the embodiments disclosed in this invention can be implemented in electronic hardware, or a combination of computer software and electronic hardware. Whether these functions are implemented in hardware or software depends on the specific application and design constraints of the technical solution. Those skilled in the art can use different methods to implement the described functions for each specific application, but such implementations should not be considered beyond the scope of this invention.

[0252] Those skilled in the art will understand that, for the sake of convenience and brevity, the specific working processes of the systems, devices, and units described above can be referred to the corresponding processes in the foregoing method embodiments, and will not be repeated here.

[0253] In the embodiments provided in this application, it should be understood that the disclosed apparatus and methods can be implemented in other ways. For example, the apparatus embodiments described above are merely illustrative. For instance, the division of units is only a logical functional division, and in actual implementation, there may be other division methods. For example, multiple units or components may be combined or integrated into another system, or some features may be ignored or not executed. Furthermore, the coupling or direct coupling or communication connection shown or discussed may be through some interfaces; the indirect coupling or communication connection between apparatuses or units may be electrical, mechanical, or other forms.

[0254] The units described as separate components may or may not be physically separate. The components shown as units may or may not be physical units; that is, they may be located in one place or distributed across multiple network units. Some or all of the units can be selected to achieve the purpose of this embodiment according to actual needs.

[0255] In addition, the functional units in the various embodiments of the present invention can be integrated into one processing unit, or each unit can exist physically separately, or two or more units can be integrated into one unit.

[0256] If the aforementioned functions are implemented as software functional units and sold or used as independent products, they can be stored in a computer-readable storage medium. Based on this understanding, the technical solution of this invention, essentially, or the part that contributes to the prior art, or a portion of the technical solution, can be embodied in the form of a software product. This computer software product is stored in a storage medium and includes several instructions to cause a computer device (which may be a personal computer, server, or network device, etc.) to execute all or part of the steps of the methods described in the various embodiments of this invention. The aforementioned storage medium includes various media capable of storing program code, such as USB flash drives, portable hard drives, ROM, RAM, magnetic disks, or optical disks.

[0257] The above description is merely a specific embodiment of the present invention, but the scope of protection of the present invention is not limited thereto. Any variations or substitutions that can be easily conceived by those skilled in the art within the technical scope disclosed in the present invention should be included within the scope of protection of the present invention. Therefore, the scope of protection of the present invention should be determined by the scope of the claims.

Claims

1. A data processing method, characterized in that, Applied to a terminal, the method includes: In a scenario where a target user uses the terminal to search for resources on a network platform, the system obtains the target user's historical search behavior data on the network platform, the target user's historical interaction behavior data on the network platform, and the target user's associated users' historical manipulation behavior data on the network platform. The associated users include users on the network platform who have a friend relationship with the target user or users in the target user's friend list on the platform account. At least one search recommendation term is obtained based on the historical search behavior data, the historical interaction behavior data, and the historical control behavior data. The historical interaction behavior data includes: interaction terms used by the target user in historical interaction scenarios and the number of times each interaction term was used. A keyword set is obtained, which includes multiple keywords determined based on the services provided by the network platform. Whenever the target user uses an interaction term in a historical interaction scenario, it is determined whether the interaction term is in the keyword set. If the interaction term is not in the keyword set, then the interaction term is unrelated to the services provided by the network platform. Specifically, if the target user has posted text comments on resources displayed on a page provided by the network platform or posted text for users to view on a page provided by the network platform, the posted text is analyzed to obtain keywords describing the topic of the posted text, and these keywords are used as interaction terms. The at least one search recommendation term is then displayed on the screen of the terminal. The step of obtaining the historical operation behavior data of the associated users of the target user on the network platform includes: The system obtains the control words used by the associated user in historical control scenarios and the number of times each control word was used; the historical control scenarios include at least historical search scenarios and / or historical interaction scenarios, and the control words include at least search terms and / or interaction terms. Historical manipulation behavior data is obtained based on the manipulation words used and the number of times each manipulation word was used. The step of obtaining the control words used by the associated user in historical control scenarios and the number of times each control word was used includes: In the third correspondence between the control words used by the associated user in historical control scenarios and the number of times the control words were used, each control word used in the historical control scenarios and the number of times each control word was used were obtained.

2. The method according to claim 1, characterized in that, The acquisition of the target user's historical search behavior data on the network platform includes: Obtain the search terms used by the target user in historical search scenarios and the number of times each search term was used; Historical search behavior data is obtained based on the search terms used and the number of times each search term was used.

3. The method according to claim 2, characterized in that, The process of obtaining historical search behavior data based on the search terms used and the frequency of use of each search term includes: In descending order of frequency of use, at least one search term is selected from the used search terms and used as the historical search behavior data.

4. The method according to claim 2, characterized in that, The step of obtaining the search terms used by the target user in historical search scenarios and the number of times each search term was used includes: In the first correspondence between the search terms used by the target user in historical search scenarios and the number of times the search terms were used, each search term used in historical search scenarios and the number of times each search term was used were obtained.

5. The method according to claim 4, characterized in that, The method further includes: Obtain a keyword set, which includes multiple keywords determined based on the services provided by the network platform; Whenever the target user uses a search term in a historical search scenario, determine whether the search term is located in the keyword set; If the search term is located in the keyword set, the search term is searched in the first correspondence. If a search term is found in the first correspondence, the usage count corresponding to the search term is increased in the first correspondence. If the search term is not found in the first correspondence, an initial value for the number of uses is set, and the search term and the initial value for the number of uses are combined into a corresponding table entry and stored in the first correspondence.

6. The method according to claim 1, characterized in that, The acquisition of the target user's historical interaction behavior data on the network platform includes: Obtain the interaction words used by the target user in historical interaction scenarios and the number of times each interaction word was used; Historical interaction behavior data is obtained based on the interaction words used and the number of times each interaction word was used.

7. The method according to claim 6, characterized in that, The process of obtaining historical interaction behavior data based on the used interaction words and the number of times each interaction word has been used includes: In descending order of usage frequency, at least one interactive word is selected from the used interactive words and used as the historical interactive behavior data.

8. The method according to claim 6, characterized in that, The step of obtaining the interaction words used by the target user in historical interaction scenarios and the number of times each interaction word was used includes: In the second correspondence between the interaction words used by the target user in the historical interaction scenario and the number of times the interaction words were used, each interaction word used in the historical interaction scenario and the number of times each interaction word was used were obtained.

9. The method according to claim 8, characterized in that, The method further includes: If the interaction word is located in the keyword set, the interaction word is searched in the second correspondence. If the interaction term is found in the second correspondence, the usage count corresponding to the interaction term is added to the first correspondence between the search terms used by the target user in historical search scenarios and the usage count of the search terms. If the interaction word is not found in the second correspondence, an initial value for the number of uses is set, and the interaction word and the initial value for the number of uses are combined into a corresponding table entry and stored in the second correspondence.

10. The method according to claim 1, characterized in that, The process of obtaining historical manipulation behavior data based on the manipulate words used and the number of times each manipulate word was used includes: In descending order of usage frequency, at least one control word is selected from the used control words and used as the historical control behavior data.

11. The method according to claim 1, characterized in that, The method further includes: For any associated user associated with the target user, obtain the first correspondence relationship and the second correspondence relationship corresponding to the associated user. The first correspondence relationship corresponding to the associated user includes the correspondence relationship between the search terms used by the associated user in historical search scenarios and the number of times the search terms were used. The second correspondence relationship corresponding to the associated user includes the correspondence relationship between the interaction terms used by the associated user in historical interaction scenarios and the number of times the interaction terms were used. For any word in the first and second correspondence relationships, the word is searched in the third correspondence relationship between the control words used by the associated user in historical control scenarios and the number of times the control words were used. If the word is found in the third correspondence, the usage count corresponding to the word is added to the third correspondence based on the usage count of the word in the first correspondence and / or the usage count of the word in the second correspondence; If the word is not found in the third correspondence, an initial value for the number of uses is set, and the word and the initial value for the number of uses are combined into a corresponding entry and stored in the third correspondence.

12. The method according to claim 1, characterized in that, The historical search behavior data includes: the search terms used by the target user in historical search scenarios and the number of times each search term was used; the historical interaction behavior data includes: the interaction terms used by the target user in historical interaction scenarios and the number of times each interaction term was used; the historical manipulation behavior data includes: the manipulation terms used by the associated user in historical manipulation scenarios and the number of times each manipulation term was used; the historical manipulation scenarios include at least historical search scenarios and / or historical interaction scenarios, and the manipulation terms include at least search terms and / or interaction terms; The step of obtaining at least one search recommendation term based on the historical search behavior data, the historical interaction behavior data, and the historical control behavior data includes: For any one of the search term, the interaction term, and the control term, the recommendation score of the term is obtained based on the number of times the target user uses the term in historical search scenarios, the number of times the target user uses the term in historical interaction scenarios, and the number of times the associated user uses the term in historical control scenarios. Based on the recommendation scores of each word among the search term, interaction term, and manipulation term, from highest to lowest, at least one word is selected as the search recommendation term.

13. The method according to claim 12, characterized in that, The step of obtaining a recommendation score for a word based on the number of times the target user uses the word in historical search scenarios, the number of times the target user uses the word in historical interaction scenarios, and the number of times the associated user uses the word in historical operation scenarios includes: Based on the number of times the target user used the word in historical search scenarios, the number of times the target user used the word in historical interaction scenarios, and the number of times the associated user used the word in historical operation scenarios, the recommendation score of the word is calculated according to the following formula: Score = w1*H + w2*C + w3*S; In the above formula, Score is the recommended score of the word, w1 is the first preset coefficient, w2 is the second preset coefficient, w3 is the third preset coefficient, H is the number of times the target user uses the word in historical search scenarios, C is the number of times the target user uses the word in historical interaction scenarios, and S is the number of times the associated user uses the word in historical control scenarios.

14. A data processing apparatus, characterized in that, Applied to a terminal, the device includes: The first acquisition module is used to acquire the target user's historical search behavior data on the network platform in the scenario where the target user uses the terminal to search for resources on the network platform. The second acquisition module is used to acquire the target user's historical interaction behavior data on the network platform. The third acquisition module is used to acquire the historical operation behavior data of the target user's associated users on the network platform. The associated users include: users on the network platform who have a friend relationship with the target user or users in the target user's friend list on the platform account. The fourth acquisition module is used to acquire at least one search recommendation term based on the historical search behavior data, the historical interaction behavior data, and the historical control behavior data. The historical interaction behavior data includes: interaction terms used by the target user in historical interaction scenarios and the number of times each interaction term was used. A keyword set is acquired, which includes multiple keywords determined based on the services provided by the network platform. Whenever the target user uses an interaction term in a historical interaction scenario, it is determined whether the interaction term is in the keyword set. If the interaction term is not in the keyword set, then the interaction term is unrelated to the services provided by the network platform. Specifically, if the target user publishes text comments on resources displayed on a page provided by the network platform or publishes text for users to view on a page provided by the network platform, the published text is analyzed to obtain keywords describing the theme of the published text, and these keywords are used as interaction terms. A display module is used to display the at least one search recommendation term on the screen of the terminal; The third acquisition module includes: The fifth acquisition unit is used to acquire the control words used by the associated user in historical control scenarios and the number of times each control word was used; the historical control scenarios include at least historical search scenarios and / or historical interaction scenarios, and the control words include at least search terms and / or interaction terms; The sixth acquisition unit is used to acquire historical manipulation behavior data based on the manipulation words used and the number of times each manipulation word was used. The fifth acquisition unit includes: The fifth acquisition subunit is used to acquire, from the third correspondence between the control words used by the associated user in the historical control scenario and the number of times the control words are used, each control word used in the historical control scenario and the number of times each control word is used.

15. The apparatus according to claim 14, characterized in that, The first acquisition module includes: The first acquisition unit is used to acquire the search terms used by the target user in historical search scenarios and the number of times each search term was used. The second acquisition unit is used to acquire historical search behavior data based on the search terms used and the number of times each search term was used.

16. The apparatus according to claim 15, characterized in that, The second acquisition unit includes: The first selection subunit is used to select at least one search term from the search terms used in descending order of usage frequency, and use it as the historical search behavior data.

17. The apparatus according to claim 15, characterized in that, The first acquisition unit includes: The first acquisition subunit is used to acquire, from the first correspondence between the search terms used by the target user in the historical search scenario and the number of times each search term was used, each search term used in the historical search scenario and the number of times each search term was used.

18. The apparatus according to claim 17, characterized in that, The first acquisition unit further includes: The first search subunit is used to search for the search term in the first correspondence when the search term is located in the keyword set; The first addition subunit is used to add the usage count corresponding to the search term in the first correspondence when the search term is found in the first correspondence. The first storage subunit is used to set an initial value for the number of uses when the search term is not found in the first correspondence, to form a corresponding table entry with the search term and the initial value for the number of uses, and to store it in the first correspondence.

19. The apparatus according to claim 14, characterized in that, The second acquisition module includes: The third acquisition unit is used to acquire the interaction words used by the target user in historical interaction scenarios and the number of times each interaction word was used. The fourth acquisition unit is used to acquire historical interaction behavior data based on the interaction words used and the number of times each interaction word was used.

20. The apparatus according to claim 19, characterized in that, The fourth acquisition unit includes: The second selection subunit is used to select at least one interaction word from the interaction words that have been used, in descending order of usage frequency, and use it as the historical interaction behavior data.

21. The apparatus according to claim 19, characterized in that, The third acquisition unit includes: The third acquisition subunit is used to acquire, from the second correspondence between the interaction words used by the target user in the historical interaction scenario and the number of times the interaction words are used, each interaction word used in the historical interaction scenario and the number of times each interaction word is used.

22. The apparatus according to claim 21, characterized in that, The third acquisition unit further includes: The fourth acquisition subunit is used to acquire a keyword set, which includes multiple keywords, and the multiple keywords are determined based on the services provided by the network platform; The second determining subunit is used to determine whether an interaction word is located in the keyword set whenever the target user uses an interaction word in a historical interaction scenario. The second search subunit is used to search for the interaction word in the second correspondence when the interaction word is located in the keyword set; The second addition subunit is used to add the usage count corresponding to the interaction word to the first correspondence between the search words used by the target user in historical search scenarios and the usage count of the search words when the interaction word is found in the second correspondence; The second storage subunit is used to set an initial value for the number of uses when the interaction word is not found in the second correspondence, to form a corresponding table entry with the interaction word and the initial value for the number of uses, and to store it in the second correspondence.

23. The apparatus according to claim 14, characterized in that, The sixth acquisition unit includes: The third selection subunit is used to select at least one control word from the control words that have been used, in descending order of usage frequency, and use it as the historical control behavior data.

24. The apparatus according to claim 14, characterized in that, The fifth acquisition unit further includes: The sixth acquisition subunit is used to acquire, for any associated user associated with the target user, a first correspondence relationship and a second correspondence relationship corresponding to the associated user. The first correspondence relationship corresponding to the associated user includes the correspondence between the search terms used by the associated user in historical search scenarios and the number of times the search terms were used. The second correspondence relationship corresponding to the associated user includes the correspondence between the interaction terms used by the associated user in historical interaction scenarios and the number of times the interaction terms were used. The third search subunit is used to search for any word in the first correspondence relationship and the second correspondence relationship in the third correspondence relationship between the control words used by the associated user in historical control scenarios and the number of times the control words were used. The third subunit is used to, when the word is found in the third correspondence, add the usage count corresponding to the word in the third correspondence according to the usage count of the word in the first correspondence and / or the usage count of the word in the second correspondence; The third storage subunit is used to set an initial value for the number of uses when the word is not found in the third correspondence, form a corresponding table entry with the word and the initial value for the number of uses, and store it in the third correspondence.

25. The apparatus according to claim 14, characterized in that, The historical search behavior data includes: the search terms used by the target user in historical search scenarios and the number of times each search term was used; the historical interaction behavior data includes: the interaction terms used by the target user in historical interaction scenarios and the number of times each interaction term was used; the historical manipulation behavior data includes: the manipulation terms used by the associated user in historical manipulation scenarios and the number of times each manipulation term was used; the historical manipulation scenarios include at least historical search scenarios and / or historical interaction scenarios, and the manipulation terms include at least search terms and / or interaction terms; The fourth acquisition module includes: The seventh acquisition unit is used to acquire a recommendation score for any one of the search terms, interaction terms, and control terms, based on the number of times the target user uses the term in historical search scenarios, the number of times the target user uses the term in historical interaction scenarios, and the number of times the associated user uses the term in historical control scenarios. The selection unit is used to select at least one word from the search term, the interaction term, and the control term as a search recommendation term, according to the recommendation scores of each word in the search term, the interaction term, and the control term in descending order.

26. The apparatus according to claim 25, characterized in that, The seventh acquisition unit is specifically used to: calculate the recommendation score of the word according to the following formula based on the number of times the target user used the word in historical search scenarios, the number of times the target user used the word in historical interaction scenarios, and the number of times the associated user used the word in historical operation scenarios: Score = w1*H + w2*C + w3*S; In the above formula, Score is the recommended score of the word, w1 is the first preset coefficient, w2 is the second preset coefficient, w3 is the third preset coefficient, H is the number of times the target user uses the word in historical search scenarios, C is the number of times the target user uses the word in historical interaction scenarios, and S is the number of times the associated user uses the word in historical control scenarios.

27. An electronic device, characterized in that, include: A processor, a memory, and a computer program stored in the memory and executable on the processor, wherein the computer program, when executed by the processor, implements the steps of the data processing method as described in any one of claims 1 to 13.

28. A computer-readable storage medium, characterized in that, The computer-readable storage medium stores a computer program that, when executed by a processor, implements the steps of the data processing method as described in any one of claims 1 to 13.

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