CN106302085B - Recommendation method and system for instant messaging group - Google Patents
Recommendation method and system for instant messaging group Download PDFInfo
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- CN106302085B CN106302085B CN201510254173.0A CN201510254173A CN106302085B CN 106302085 B CN106302085 B CN 106302085B CN 201510254173 A CN201510254173 A CN 201510254173A CN 106302085 B CN106302085 B CN 106302085B
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Abstract
The invention relates to a recommendation method and a system for an instant messaging group, wherein the method comprises the following steps: receiving operation information of a user; analyzing the operation information to determine the category of the operation information; searching an instant communication group matched with the category, wherein the category of the instant communication group is determined by analyzing the chat content in the group in real time; and outputting recommendation information for recommending the instant communication group to the user. The system comprises a receiving module, an analysis module, a searching module and an output module. According to the method and the device, the operation information is analyzed, the category of the operation information is determined, the instant communication group matched with the category is searched and recommended to the user, a complicated searching process is omitted, the instant communication group related to the user is recommended to the user actively, and the method and the device are very convenient and fast.
Description
Technical Field
The present invention relates to the field of communications, and in particular, to a method and a system for recommending an instant messaging group.
Background
With the development of society, the popularization speed of the internet is faster and faster, and the communication between people is realized through the internet more. The most common internet services for people include various instant messaging services based on terminal devices such as computers and mobile phones, and the instant messaging services bring great convenience to communication of people.
With the increasing pace of life and the increasing demand for diversification, people always want to quickly acquire information that they are interested in or pay much attention to. Particularly, in the instant messaging service, people want to quickly join in groups in the instant messaging service according to their interests or concerns to interact with people who have common interests or concerns among the groups. In order to find out the corresponding instant messaging group, the user needs to search through the keywords or search one by one according to categories, and then the instant messaging group meeting the requirements is displayed according to the search conditions or the selected categories of the user, so that the operation is very complicated.
Disclosure of Invention
Therefore, it is necessary to provide a method and a system for recommending an instant messaging group, aiming at the problem of complicated searching operation of the instant messaging group.
A recommendation method for instant communication group includes the following steps:
receiving operation information of a user;
analyzing the operational information to determine a category of the operational information;
searching an instant communication group matched with the category, wherein the category of the instant communication group is determined by analyzing the chat content in the group in real time; and
and outputting recommendation information for recommending the instant communication group to the user.
A recommendation system for an instant messaging group, comprising:
the receiving module is used for receiving the operation information of a user;
an analysis module to analyze the operational information to determine a category of the operational information;
the searching module is used for searching the instant communication group matched with the category, and the category of the instant communication group is determined by analyzing the chat content in the group in real time; and
and the output module is used for outputting recommendation information for recommending the instant communication group to the user.
According to the method and the system for recommending the instant messaging group, the operation information is analyzed to determine the category of the operation information, then the instant messaging group matched with the category is searched and recommended to the user, the tedious searching process is omitted, the instant messaging group related to the user is actively recommended to the user, and the method and the system are very convenient and fast. The category of the instant messaging group is determined by analyzing the chat content in the group in real time, so that the found recent chat content in the instant messaging group is related to the category of the operation information and has higher activity, and the recent chat content has the content related to the category of the operation information if a user joins the instant messaging group, thereby avoiding wrong recommendation or temporary failure due to the fact that the recommended recent activity of the instant messaging group is not high and the group chat content is not related to the category of the operation information or the group chat content is not related to the category of the operation information.
Drawings
FIG. 1 is a flowchart illustrating a method for recommending an instant messaging group according to an embodiment;
FIG. 2 is a detailed flowchart of step S180 in FIG. 1;
FIG. 3 is a flowchart illustrating a method for recommending an instant messaging group according to another embodiment;
FIG. 4 is a detailed flowchart of step S160 in FIG. 1;
FIG. 5 is a flowchart illustrating a method for recommending an instant messaging group according to yet another embodiment;
FIG. 6 is a schematic view of an interface when a user inputs operation information;
FIG. 7 is a schematic diagram of an interface for reminding a user to join a recommended group;
FIG. 8 is a schematic diagram of a group recommendation interface displayed after a user opens the group notification prompt box in FIG. 7;
FIG. 9 is a block diagram of a recommendation system for an instant messaging group according to an embodiment;
FIG. 10 is a block diagram of the lookup module of FIG. 9;
FIG. 11 is a block diagram of the output module of FIG. 9;
FIG. 12 is a block diagram of a recommendation system for an instant messaging group according to another embodiment;
FIG. 13 is a diagram of a recommendation system for an instant messaging group according to yet another embodiment;
FIG. 14 is a block diagram of a computer system capable of implementing embodiments of the present invention.
Detailed Description
In order to make the objects, technical solutions and advantages of the present invention more apparent, the present invention is described in further detail below with reference to the accompanying drawings and embodiments. It should be understood that the specific embodiments described herein are merely illustrative of the invention and are not intended to limit the invention.
Unless the context clearly dictates otherwise, the elements and components of the present invention may be present in either single or in multiple forms and are not limited thereto. Although the steps in the present invention are arranged by using reference numbers, the order of the steps is not limited, and the relative order of the steps can be adjusted unless the order of the steps is explicitly stated or other steps are required for the execution of a certain step. It is to be understood that the term "and/or" as used herein refers to and encompasses any and all possible combinations of one or more of the associated listed items.
As shown in fig. 1, a method for recommending an instant messaging group according to an embodiment includes steps S120 to S180.
Step S120, receiving operation information of the user. The operation information of the user may be operation information in the instant messaging application, for example, the user has searched a keyword in a search panel of the instant messaging application, the user has participated in a campaign advertised by a certain instant messaging application, the user has published or answered a topic discussed by an organization of a certain instant messaging application, and the like. In addition, the operation information of the user may not be limited to the instant messaging application, and may be included in the range of the operation information as long as the operation information can help to accurately judge the user preference and is favorable for the behavior of group recommendation accuracy, such as game playing, music listening, web browsing operation, and the like. The operation information of the user may be real-time operation information or non-real-time operation information. In the embodiment, the operation information of the user is real-time operation information so as to have better instantaneity and overcome the problems that the interest change of the user cannot be accurately mastered by off-line calculation, the recommendation period is too long and the recommendation is inaccurate.
Step S140, analyzing the operation information to determine the category of the operation information. The category is a predefined category and can be a certain sports item, such as football or badminton; or may be a specialized technology such as touch screen technology or camera technology. The operation information of the user can be analyzed, for example, a search keyword input by the user is matched with a keyword in a predefined category, and if the matching is successful, the corresponding operation information can be determined as the category of the successful matching. Similarly, when playing games and listening to music, the corresponding categories can be correspondingly matched through game names or types, song names or song styles of the music. In addition to determining the category of the operation information by analyzing the operation information, the category of the operation information may be more accurately determined by being assisted by big data analysis associated with a user. The big data analysis associated with the user can be used for analyzing relationship chain data of the user on the internet, such as instant messaging friend relationship chain data, forum friend relationship chain data and the like, and the category of the operation information is determined more accurately according to friend interests and hobbies on the relationship chain; the big data analysis associated with the user can also be used for more accurately determining the category of the operation information by analyzing the network behaviors of the members in the instant messaging group which the user already joins, or analyzing the network behaviors of friends of the user and the like. That is, in step S140 of analyzing the operation information to specify the type of the operation information, the type of the operation information may be directly specified by analyzing only the operation information, or the type of the operation information may be specified by analyzing the operation information and the big data related to the user.
Step S160, find the instant messaging group matching the category.
After the category of the operation information is determined, the instant communication group matched with the category can be directly searched according to the category of the operation information. For example, if the operation information category of the user is analyzed to be a science fiction movie in step S140, the instant messaging group associated with the science fiction movie is directly searched. The category of the instant messaging group may be determined by analyzing an existing instant messaging group. Such as by analyzing chat content within the group in real-time. The category of the instant messaging group is determined by analyzing the chat content in the group in real time, so that the found recent chat content in the instant messaging group is related to the category of the operation information and has higher activity, and the recent chat content has the content related to the category of the operation information if a user joins the instant messaging group, thereby avoiding wrong recommendation or temporary failure due to the fact that the recommended recent activity of the instant messaging group is not high and the group chat content is not related to the category of the operation information or the group chat content is not related to the category of the operation information. In addition, the type of the instant messaging group can be determined by analyzing one or more of group labels, group types, group profiles and main interests of users in the group, and more reference factors are introduced through the analysis to further improve the accuracy of determining the type of the instant messaging group. Because the number of the timely communication groups is very large, the data volume related to the chat content, the group label, the group type, the group profile and the main interest of the users in the group is extremely large, and a large data analysis method can be adopted.
And step S180, outputting recommendation information for recommending the instant communication group to the user. For example, a message may be popped up in a message bar of the instant messaging application, and brief information of a recommended instant messaging group, such as a group tag, a group type, a group profile, etc., is provided for the user to refer to whether to join. Specifically, as shown in fig. 2, step S180 may include step S182 and step S184.
Step S182, a push channel for real-time pushing between the server and the client is established. Through the push channel, the information of the server side can be pushed to the client side in real time. The user may also feed back likes or dislikes of the recommendation group in real time.
Step S184, sending the recommendation information recommended to the user by the instant communication group to the client through the push channel and activating the client to remind the user. For example, the user can be reminded through a red point system, which is a system capable of strongly reminding the user at present on a mobile phone, so that the user can be reminded of new recommended data delivery through a prompt tone, an indicator light or screen display and the like.
According to the recommendation method of the instant messaging group, the operation information is analyzed, the category of the operation information is determined, then the instant messaging group matched with the category is searched and recommended to the user, the tedious search process is omitted, the instant messaging group related to the user is actively recommended to the user, and the recommendation method is very convenient and fast.
As shown in fig. 3, the method for recommending an instant messaging group according to another embodiment further includes step S130: location information of a user is acquired. The location information of the user may be determined according to the IP address of the user or the GPS latitude and longitude, etc. At this time, the step S160 is to search for the instant messaging group matching with the category and the location information. That is, by the embodiment, not only the instant messaging groups with the matched categories can be found, but also the instant messaging groups with the same or similar positions, such as the instant messaging groups in the same city or the same area, can be found.
In addition, in step S160, except that after the category of the operation information is determined, the instant messaging group matching the category is directly searched according to the category of the operation information, as shown in fig. 4, in the method for recommending an instant messaging group according to another embodiment, step S160 includes step S162 to step S164.
And step S162, establishing a category table of the operation information and scoring the category of the corresponding operation information. For example, the category of the operation information includes the categories of badminton, hollywood movie, travel, securities, etc., and the categories are established into a table, and if the category of the operation information determined after each step S140 is executed is not in the category table of the operation information, the category of the corresponding operation information can be created; the category of the operation information determined after each execution of step S140 may increase the score of the category of the corresponding operation information if it is already in the category table of the operation information. That is, if the more the user's same kind of operation information, the higher the category score of the corresponding operation information.
And step S164, selecting the category of the operation information in the category table according to the score obtained by scoring, and searching the instant communication group matched with the category. Specifically, the category of the operation information with the highest score in the category table may be selected, and the number of selections may be one category or two categories, or the like. In addition, in order to avoid too similar categories of the instant messaging groups searched each time, the categories with scores meeting the predetermined requirement (for example, 10 top ranked names) can be randomly selected, and the probability of being selected is configured to be higher the ranking is.
Through the steps of S162 and S164, the interest lists of the categories corresponding to different operation information of the user can be obtained according to the categories of the operation information of the user, the interests of the user are ranked, and the interests of the user are accurately located according to the changes of the conditions such as the age, the behavior and the like of the user, so that the recommended instant messaging groups are more diversified, and the instant messaging groups which are not concerned by the user cannot be recommended due to the occasional random operation information of the user.
As shown in fig. 5, the method for recommending an instant messaging group according to another embodiment further includes steps S192 through S196.
Step S192, judging whether the user joins the recommended instant communication group aiming at the recommended information.
Step S194, if the user joins the recommended instant messaging group, increasing the score of the category of the corresponding operation information. If the user joins the recommended instant communication group, the recommended instant communication group is popular with the user, and the score of the category of the corresponding operation information can be increased so as to recommend the same type of instant communication group next time.
Step S196, if the user refuses to join the recommended instant communication group, the score of the category of the corresponding operation information is reduced. If the user refuses to join the recommended instant communication group, the recommended instant communication group is not welcomed by the user, the grade of the corresponding operation information can be reduced, the probability of recommending the same kind of instant communication group is reduced, and the recommending effect is more suitable for the user.
The above-described method is described in further detail below with reference to the specific schematic diagrams shown in fig. 6, 7 and 8. As shown in fig. 6, when the user is interested in knowledge of stocks, the user may input a keyword "stock" and perform an instant messaging group search to obtain N stock recommendation groups, such as "stock", "stock disk recommendation group", "stock help platform", "stock opening", "stock funding", "Shenzhen stock exchange", "stock exchange in black horse market", and the like, which all have different functions, for example, some of which help opening an account, some of which provide stock selection technology, some of which help people exchange study, and the like, and only some of which may accord with the user's selection. The operation information of searching the instant communication group containing 'stock' indicates the interest of the user. The operation information of the user may be received through step S120 of the above method. After receiving the operation information for searching the instant messaging group containing "stock", the operation information may be analyzed to determine the corresponding category through step S140 of the above method, and the category corresponding to the keyword "stock" may be the categories of investment, securities, etc., which may be predefined in advance. When determining the category of the operation information of the instant messaging group containing "stock", the "stock" may be used as a keyword to compare with the keywords contained in each category, so as to determine the category to which the operation information of the instant messaging group containing "stock" corresponds, for example, determine that the operation information is a stock category. After determining that the type of the operation information for searching the instant messaging group containing "stock" is a stock type, according to step S160, an instant messaging group matching the stock type is searched. The categories of a large number of instant messaging groups existing in the network can be determined through big data analysis, wherein the instant messaging groups belonging to the security category are searched for in step S160, and then recommendation information is output in step S180 to recommend the instant messaging groups of the security category to the user. It is to be understood that the instant messaging group recommended herein may be a part or all of the instant messaging groups under the corresponding category. As shown in fig. 7, the recommendation information output in step S180 may be in a form of a group notification issued by the bonus system to remind 4 stock groups recommended to the user, and the 4 stock groups may be displayed by opening the group notification by the user, as shown in fig. 8, the 4 stock groups may be "shenzhen stock exchange", "stock opening commission ten thousand", "stock market research analysis institute", and "stock market teller-a stock equity". At this point, the user may choose to join any one or more of these 4 groups.
The technical features of the embodiments described above may be arbitrarily combined, and for the sake of brevity, all possible combinations of the technical features in the embodiments described above are not described, but should be considered as being within the scope of the present specification as long as there is no contradiction between the combinations of the technical features.
As shown in fig. 9, an embodiment of the recommendation system for an instant messaging group includes a receiving module 120, an analyzing module 140, a searching module 160, and an outputting module 180.
The receiving module 120 is used for receiving operation information of a user. The operation information of the user can be operation information in the instant messaging application. The operation information of the user can be that the user searches a certain keyword on a search panel of the instant messaging application, the user participates in a certain campaign advertised by the instant messaging application, the user issues or answers a topic discussed by an organization of the instant messaging application, and the like. In addition, the operation information of the user may not be limited to the instant messaging application, and may be included in the range of the operation information as long as the operation information can help to accurately judge the user preference and is favorable for the behavior of group recommendation accuracy, such as game playing, music listening, web browsing operation, and the like. The operation information of the user may be real-time operation information or non-real-time operation information. In the embodiment, the operation information of the user is real-time operation information so as to have better instantaneity and overcome the problems that the interest change of the user cannot be accurately mastered by off-line calculation, the recommendation period is too long and the recommendation is inaccurate.
The analysis module 140 is configured to analyze the operation information to determine a category of the operation information. The category is a predefined category and can be a certain sports item, such as football or badminton; or may be a specialized technology such as touch screen technology or camera technology. The operation information of the user can be analyzed, for example, a search keyword input by the user is matched with a keyword in a predefined category, and if the matching is successful, the corresponding operation information can be determined as the category of the successful matching. Similarly, when playing games and listening to music, the corresponding categories can be correspondingly matched through game names or types, song names or song styles of the music. The analysis module 140 may determine the category of the operation information more precisely by analyzing the operation information, in addition to determining the category of the operation information by analyzing the operation information, and by analyzing big data associated with a user. The big data analysis associated with the user can be used for analyzing relationship chain data of the user on the internet, such as instant messaging friend relationship chain data, forum friend relationship chain data and the like, and the category of the operation information is determined more accurately according to friend interests and hobbies on the relationship chain; the big data analysis associated with the user can also be used for more accurately determining the category of the operation information by analyzing the network behaviors of the members in the instant messaging group which the user already joins, or analyzing the network behaviors of friends of the user and the like. That is, the analysis module 140 may analyze only the operation information to directly determine the type of the operation information, or may analyze the operation information and the big data associated with the user to determine the type of the operation information.
The searching module 160 is used for searching the instant communication group matched with the category.
In one embodiment, after the category of the operation information is determined, the searching module 160 may directly search the instant messaging group of the matching category according to the category of the operation information. For example, if the operation information category of the user is analyzed as the science fiction movie by the analysis module 140, the instant messaging group related to the science fiction movie is directly searched. The category of the instant messaging group may be determined by analyzing an existing instant messaging group. Such as by analyzing chat content within the group in real-time. The category of the instant messaging group is determined by analyzing the chat content in the group in real time, so that the found recent chat content in the instant messaging group is related to the category of the operation information and has higher activity, and the recent chat content has the content related to the category of the operation information if a user joins the instant messaging group, thereby avoiding wrong recommendation or temporary failure due to the fact that the recommended recent activity of the instant messaging group is not high and the group chat content is not related to the category of the operation information or the group chat content is not related to the category of the operation information. In addition, the search module 160 may further determine the category of the instant messaging group by analyzing one or more of the group tag, the group type, the group profile, and the main interest of the user in the group, and further improve the accuracy of determining the category of the instant messaging group by introducing more reference factors through the analysis. Because the number of the timely communication groups is very large, the data volume related to the chat content, the group label, the group type, the group profile and the main interest of the users in the group is extremely large, and a large data analysis method can be adopted.
In another embodiment, as shown in fig. 10, the search module 160 includes a scoring unit 162 and a search unit 164.
The scoring unit 162 is configured to establish a category table of the operation information and score the category of the corresponding operation information. For example, the category of the operation information includes the categories of badminton, hollywood movie, tourism, securities, etc., which are tabulated, and if the category of the operation information determined by the analysis module 140 is not in the category table of the operation information, the scoring unit 162 may create the category of the corresponding operation information; the classification of the operation information determined by the analysis module 140 may increase the score of the classification of the corresponding operation information if it is already in the classification table of the operation information. That is, if the more the user's same kind of operation information, the higher the category score of the corresponding operation information.
The searching unit 164 is configured to select a category of the operation information in the category table according to the score obtained by the scoring, and search for an instant messaging group matching the category. Specifically, the category of the operation information with the highest score in the category table may be selected, and the number of selections may be one category or two categories, or the like. In addition, in order to avoid too similar categories of the instant messaging groups searched each time, the categories with scores meeting the predetermined requirement (for example, 10 top ranked names) can be randomly selected, and the probability of being selected is configured to be higher the ranking is.
Through the scoring unit 162 and the searching unit 164, the interest lists of the categories corresponding to different operation information of the user can be obtained according to the categories of the operation information of the user, the interests of the user are ranked, and the interests and hobbies of the user are accurately positioned according to the changes of the conditions such as the age, the behavior and the like of the user, so that the recommended instant messaging groups are more diversified, and the instant messaging groups which are not concerned by the user cannot be recommended due to the occasional random operation information of the user.
The output module 180 is configured to output recommendation information for recommending the instant messaging group to the user. For example, a message may be popped up in a message bar of the instant messaging application, and brief information of a recommended instant messaging group, such as a group tag, a group type, a group profile, etc., is provided for the user to refer to whether to join. Specifically, as shown in fig. 11, the output module 180 includes a channel establishing unit 182 and a pushing unit 184.
The channel establishing unit 182 is configured to establish a push channel for real-time pushing between the server and the client. Through the push channel, the information of the server side can be pushed to the client side in real time. The user may also feed back in real time whether the recommendation group is liked or disliked.
The pushing unit 184 is configured to send recommendation information recommended to the user by the instant messaging group to the client through the pushing channel and activate the client to remind the user. For example, the user can be reminded through a red point system, which is a system capable of strongly reminding the user at present on a mobile phone, so that the user can be reminded of new recommended data delivery through a prompt tone, an indicator light or screen display and the like.
According to the recommendation system of the instant messaging group, the operation information is analyzed, the category of the operation information is determined, then the instant messaging group matched with the category is searched and recommended to the user, the tedious search process is omitted, the instant messaging group related to the user is actively recommended to the user, and the recommendation system is very convenient and fast.
In addition, as shown in fig. 12, the recommendation system for an instant messaging group according to another embodiment further includes a location information obtaining module 130. The location information acquiring module 130 is used for acquiring location information of a user. The location information of the user may be determined according to the IP address of the user or the GPS latitude and longitude, etc. At this time, the searching module 160 is configured to search for the instant messaging group matching with the category and the location information. That is, by the embodiment, not only the instant messaging groups with the matched categories can be found, but also the instant messaging groups with the same or similar positions, such as the instant messaging groups in the same city or the same area, can be found.
In addition, as shown in fig. 13, the system for recommending an instant messaging group according to another embodiment further includes a determining module 192, an adding module 194, and a subtracting module 196.
The determining module 192 is configured to determine whether the user joins the recommended instant messaging group according to the recommended information.
The scoring module 194 is configured to increase the score of the category of the corresponding operation information when the user joins the recommended instant messaging group. If the user joins the recommended instant communication group, the recommended instant communication group is popular with the user, and the score of the category of the corresponding operation information can be increased so as to recommend the same type of instant communication group next time.
The deduction module 196 is configured to reduce the score of the category of the corresponding operation information when the user refuses to join the recommended instant messaging group. If the user refuses to join the recommended instant communication group, the recommended instant communication group is not welcomed by the user, the grade of the corresponding operation information can be reduced, the probability of recommending the same kind of instant communication group is reduced, and the recommending effect is more suitable for the user.
FIG. 14 is a block diagram of a computer system 1000 upon which embodiments of the present invention may be implemented. The computer system 1000 is only one example of a suitable computing environment for the invention and is not intended to suggest any limitation as to the scope of use of the invention. Neither should the computer system 1000 be interpreted as having a dependency or requirement relating to a combination of one or more components of the exemplary computer system 1000 illustrated.
The computer system 1000 shown in FIG. 14 is one example of a computer system suitable for use with the invention. Other architectures with different subsystem configurations may also be used. Devices such as desktop computers, notebook computers, personal digital assistants, smart phones, tablet computers, and the like, as are well known to those of ordinary skill, may be suitable for use in some embodiments of the present invention. But are not limited to, the devices listed above.
As shown in fig. 14, the computer system 1000 includes a processor 1010, a memory 1020, and a system bus 1022. Various system components including the memory 1020 and the processor 1010 are connected to the system bus 1022. The processor 1010 is a piece of hardware for executing computer program instructions through basic arithmetic and logical operations in a computer system, and can execute instructions including the recommended methods of the instant messaging group. The memory 1020 is a physical device for temporarily or permanently storing a calculation program or data (e.g., program status information), and may store intermediate data generated in the above recommendation method for the instant messaging group, and the like. The processor 1010 and the memory 1020 may be in data communication via a system bus 1022. Wherein memory 1020 includes Read Only Memory (ROM) or flash memory (neither shown), and Random Access Memory (RAM), which typically refers to main memory loaded with an operating system and application programs.
The computer system 1000 also includes a display interface 1030 (e.g., a graphics processing unit), a display device 1040 (e.g., a liquid crystal display), an audio interface 1050 (e.g., a sound card), and an audio device 1060 (e.g., speakers). Display device 1040 and audio device 1060 are media devices for experiencing multimedia content. The display device 1040 may display the interfaces as shown in fig. 6, 7, 8.
As described in detail above, the computer system 1000 adapted to the present invention can perform the specified operation of the recommendation method for an instant messenger group. The computer system 1000 performs these operations in the form of software instructions executed by the processor 1010 in a computer-readable medium. These software instructions may be read into memory 1020 from storage device 1070 or from another device via local network interface 1100. The software instructions stored in the memory 1020 cause the processor 1010 to perform the above-described method for recommending an instant messaging group. Furthermore, the present invention can be implemented by hardware circuits or by a combination of hardware circuits and software instructions. Thus, implementations of the invention are not limited to any specific combination of hardware circuitry and software.
The above-mentioned embodiments only express several embodiments of the present invention, and the description thereof is more specific and detailed, but not construed as limiting the scope of the present invention. It should be noted that, for a person skilled in the art, several variations and modifications can be made without departing from the inventive concept, which falls within the scope of the present invention. Therefore, the protection scope of the present patent shall be subject to the appended claims.
Claims (12)
1. A recommendation method for instant communication group is characterized by comprising the following steps:
receiving operation information of a user;
determining the category of the operation information according to the interest and hobbies of friends on the relation chain; or analyzing the network behaviors of the members in the joined instant messaging group to determine the category of the operation information; or analyzing the network behavior of the friend to determine the category of the operation information;
establishing a category table corresponding to the operation information, and scoring each category in the category table according to the category of the operation information;
randomly selecting a preset number of categories from the category table according to the scores obtained by scoring, and searching the instant messaging groups matched with the categories;
outputting recommendation information recommending the instant communication group to the user;
when the user joins the recommended instant communication group, increasing the grade of the grade corresponding to the corresponding operation information in the grade table;
and when the user refuses to join the recommended instant communication group, reducing the grade score corresponding to the corresponding operation information in the grade table.
2. The method of claim 1, wherein the operation information of the user is operation information in an instant messaging application.
3. The method of claim 1, wherein the category of the instant messenger group is further determined by analyzing one or more of a group tag, a group type, a group profile, and a user's primary interest in the group.
4. The method as claimed in claim 1, further comprising a step of obtaining location information of the user, wherein the step of searching for the instant messaging group matching the category is to search for the instant messaging group matching the category and the location information.
5. The method as claimed in claim 1, wherein when searching for the instant messaging group matching the category, the method directly searches for the instant messaging group matching the category according to the category of the operation information.
6. The method of claim 1, wherein the step of outputting recommendation information for recommending the instant messaging group to the user comprises:
establishing a push channel for pushing a server side and a client side in real time; and
and sending recommendation information recommended to the user by the instant communication group to a client through the push channel and activating the client to remind the user.
7. A system for recommending an instant messaging group, comprising:
the receiving module is used for receiving the operation information of a user;
the analysis module is used for determining the category of the operation information according to the interest and hobbies of friends on the relationship chain; or analyzing the network behaviors of the members in the joined instant messaging group to determine the category of the operation information; or analyzing the network behavior of the friend to determine the category of the operation information;
the scoring unit is used for establishing a category table corresponding to the operation information and scoring each category in the category table according to the category of the operation information;
the searching module is used for randomly selecting a preset number of categories from the category table according to the scores obtained by scoring and searching the instant communication groups matched with the categories;
the output module is used for outputting recommendation information for recommending the instant communication group to the user;
the scoring module is used for increasing the score of the category corresponding to the corresponding operation information in the category table when the user joins the recommended instant messaging group;
and the score reducing module is used for reducing the scores of the categories corresponding to the corresponding operation information in the category table when the user refuses to join the recommended instant messaging group.
8. The system of claim 7, wherein the operation information of the user is operation information in an instant messaging application.
9. The system of claim 7, wherein the search module further determines the category of the instant messaging group by analyzing one or more of a group tag, a group type, a group profile, and a user's primary interest in the group.
10. The system of claim 7, further comprising:
the position information acquisition module is used for acquiring the position information of the user;
when searching the instant communication group matched with the category, the searching module specifically searches the instant communication group matched with the category and the position information.
11. The system as claimed in claim 7, wherein when searching for the instant messaging group matching with the category, the instant messaging group matching with the category is directly searched for according to the category of the operation information.
12. The system of claim 7, wherein the output module comprises:
the channel establishing unit is used for establishing a push channel for real-time pushing of the server and the client; and
and the pushing unit is used for sending the recommendation information recommended to the user by the instant communication group to the client through the pushing channel and activating the client to remind the user.
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