CN114817730B - Information activity information recommendation system and method under big data situation - Google Patents
Information activity information recommendation system and method under big data situation Download PDFInfo
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Abstract
The invention discloses an information activity information recommendation system and method under a big data situation. The invention can collect and input the search data, stay the watch time and repeat the watch times in real time through the user search data; extracting keywords of the activity information, matching the same kind of activity information according to the keywords and the similar keywords, and pushing the same and similar keyword information activity information quantity; analyzing and judging the number of the follow-up information activity information recommendations according to the stay viewing time of the user on the information and the viewing times of the information activity information, and adjusting the number of the information activity information recommendations in real time; after the search and the check are interrupted, the information is in a locked state, the recommended quantity of the similar activity information is directly and greatly reduced, meanwhile, the recommended quantity is adjusted in real time according to the follow-up data of the user, and when the reference quantity reaches a critical point, the locked state is released.
Description
Technical Field
The invention relates to the technical field of data processing, in particular to an information activity information recommendation system and method under a big data situation.
Background
The information is information which can bring value to the user in a relatively short time because the user timely obtains the information and utilizes the information, the information is time-efficient and regional, and the information must be utilized by consumers. In a strict sense, news is information, which is information, and not only news but also other media are covered; the information includes the category of news, supply and demand, dynamics, technology, policy, comments, views and academia, and the timeliness range is far wider than news. News is relatively broad in targeted audience, without strict audience segmentation, and information is relatively strong in targeted audience. Big data means that the data volume involved is so large that the data cannot be retrieved, managed, processed and consolidated in a reasonable time through the mainstream software tools, thus becoming more positive information for helping business operation decisions. The value of big data is manifested in several aspects: enterprises providing products or services for a large number of consumers can utilize the big data to carry out accurate marketing; the small and medium-sized micro enterprises in the small and beautiful mode can use the big data to perform service transformation; conventional businesses that face the changes that must be made under the pressure of the internet need to make full use of the value of large data over time.
The existing information activity information recommendation system based on the big data situation often pushes a large amount of information activity information aiming at user retrieval information; after the user finishes searching, whether the client still needs the information or not, the activity information is still recommended to the user, and the recommendation accuracy is poor.
Disclosure of Invention
The present invention is directed to a system and a method for recommending information of information activity under big data situation, so as to solve the problems set forth in the background art.
In order to solve the technical problems, the invention provides the following technical scheme: the information activity information recommendation system under the big data situation comprises a cloud platform, a data acquisition module, a data analysis module, an information management module, a database and an intelligent terminal, wherein the output end of the cloud platform is respectively connected with the input ends of the data acquisition module, the data analysis module, the information management module, the database and the intelligent terminal, and the input end of the cloud platform is respectively connected with the output ends of the data acquisition module, the data analysis module, the information management module, the database and the intelligent terminal; the cloud platform is used for integrally and comprehensively controlling the system, the data acquisition module is used for acquiring user retrieval information and information checking time and times of users, the data analysis module is used for extracting key words and information and carrying out modeling processing, the information management module is used for recommending, locking and unlocking the information, and the database is used for storing and referring to system data; the intelligent terminal is used for displaying, setting and adjusting system data.
Further, the cloud platform includes: the system comprises a central processing unit and an information receiving and transmitting unit, wherein the central processing unit performs comprehensive analysis processing on data, and the information receiving and transmitting unit performs receiving and transmitting processing on data information.
Further, the data acquisition module includes: the system comprises a retrieval acquisition unit, a time acquisition unit and a frequency acquisition unit; the search acquisition unit is used for acquiring search data input by a user, and the time acquisition unit is used for acquiring the stay watching time of the user in the existing information activity information and the frequency acquisition unit is used for acquiring the repeated watching times of the same kind of information activity information.
Further, the data analysis module includes: a keyword extraction unit, an information extraction unit and a model modeling unit; the keyword extraction unit analyzes and extracts keywords of the information, the information extraction unit extracts the information according to the information keywords, and the model modeling unit establishes an information recommendation model according to information recommendation data.
Further, the information management module includes: an information recommending unit, an information locking unit and an information unlocking unit; the information recommending unit recommends information, the information locking unit locks and pushes the information, and the information unlocking unit unlocks and pushes the information.
Further, the database comprises a storage unit, and the storage unit comprises a local memory and a cloud memory.
Further, the intelligent terminal comprises an input unit and a display unit, wherein the input unit is used for inputting, setting and adjusting system data by a user, and the display unit is used for displaying the system data.
The invention also provides a use method of the information activity information recommendation system under the big data situation, which comprises the following steps:
s1, starting a system through the intelligent terminal, acquiring search words of user search information by the data acquisition module, recommending information activity information according to the search words of the user, and acquiring data by the data acquisition module in a database to acquire historical stay watching time A of the user in the existing information activity information of the same key word information i Historical repeat viewing times B of identical keyword information activity information i The method comprises the steps of carrying out a first treatment on the surface of the Historical stay viewing time C for collecting approximate keyword information activity information i Historical repeat viewing count D of approximate keyword information activity information i ；
S2, the data analysis module extracts keywords of the activity information, retrieves and extracts information in the database according to the keywords and approximate or synonymous words and sentences of the keywords, determines the same keyword information activity information and approximate keyword information activity information, establishes an information recommendation model according to the front and rear data information, and comprises the following steps: the number of pushing same keyword information activity information is E, G, while the number of pushing approximate keyword information activity information is F, H;
s3, when the user checks the search information, pushing the same keyword information activity information to be E according to the user search data, and pushing the approximate keyword information activity information to be F;
T i for the average time spent for historically viewing the corresponding information activity information, n is the number of historically viewing the corresponding information activity information, t i For the average time spent on historically viewing the corresponding information activity information, m is the number of historically viewing the corresponding information activity information, and X is the total number of information activity information that can be displayed by the current search detection interface;
s4, when the user exits from checking the search information and checks the information under the condition of no other search tasks, entering an information locking state: pushing the same keyword information activity information to be G according to the user retrieval data, and pushing the approximate keyword information activity information to be H;
G＝E*(z*0.1)；
j is more than or equal to 1 and less than 4; j is the watching quantity of the information activity information of the same keyword information of the current interface;
H＝F*(y*0.1)；
k is more than or equal to 1 and less than 4; k is the watching quantity of the current interface approximate keyword information activity information;
when j is more than or equal to 4, unlocking the same keyword information lock, and pushing the same keyword information activity information to be E;
when k is more than or equal to 4, unlocking the approximate keyword information lock, and pushing the approximate keyword information activity information to be F;
s5, data in the system are collected in the cloud platform, the data in the system are stored in a database in real time, and a user can input the data through the intelligent terminal to input setting and correcting the user' S own preference and habit.
Further, in the working movement process of the system, the data is updated in real time, and the calculation formula is supplemented in real time.
Further, after the user completely exits the information activity information application, and then enters the application later, according to the recommended information activity information of the previous search keywords, the recommended number of the information activity information of the corresponding keywords is P, and the recommended number of the information activity information of the corresponding similar keywords is Q; x is the total number of information activity information which can be displayed by the current search detection interface;
Compared with the prior art, the invention has the following beneficial effects:
1. the invention can collect input search data in real time through user search data, collect stay watching time of users in the existing information activity information in real time, and repeat watching times of the same kind of information activity information by arranging the data collection module, the data analysis module, the information management module and the database; extracting keywords of the activity information, and pushing the same keyword information activity information quantity and similar keyword information activity information quantity according to matching of the keywords and similar or synonymous words and sentences of the keywords; according to the stay viewing time of the user on the information and the viewing times of the information activity information, analyzing and judging the number of the follow-up information activity information recommendations, and adjusting the number of the information activity information recommendations in real time.
2. After searching and searching are interrupted, the information locking state is entered, the recommended quantity of the same kind of activity information is directly and greatly reduced, meanwhile, the recommended quantity is adjusted in real time according to the follow-up data of the user, and when the reference quantity reaches a critical point, the locking state is released; meanwhile, determining the information quantity of recommended activities according to the watching habit of the user; when the user completely exits the information activity information application and subsequently reenters the application, the information quantity of the information activity of the corresponding keyword and the information pushing quantity of the information activity of the corresponding similar keyword are automatically recommended according to the information of the recommended information activity of the previous search keyword.
Drawings
The accompanying drawings are included to provide a further understanding of the invention and are incorporated in and constitute a part of this specification, illustrate the invention and together with the embodiments of the invention, serve to explain the invention. In the drawings:
FIG. 1 is a schematic diagram of a modular connection in the present invention;
in the figure: 1. a cloud platform; 2. a data acquisition module; 3. a data analysis module; 4. an information management module; 5. a database; 6. an intelligent terminal; 7. a central processing unit; 8. an information receiving and transmitting unit; 9. retrieving and collecting units; 10. a time acquisition unit; 11. a frequency acquisition unit; 12. a keyword extraction unit; 13. an information extraction unit; 14. a model modeling unit; 15. an information recommendation unit; 16. an information locking unit; 17. an information unlocking unit; 18. a storage unit; 19. an input unit; 20. and a display unit.
Detailed Description
The following description of the embodiments of the present invention will be made clearly and completely with reference to the accompanying drawings, in which it is apparent that the embodiments described are only some embodiments of the present invention, but not all embodiments. All other embodiments, which can be made by those skilled in the art based on the embodiments of the invention without making any inventive effort, are intended to be within the scope of the invention.
Referring to fig. 1, the present invention provides the following technical solutions: the information activity information recommendation system under the big data situation comprises a cloud platform 1, a data acquisition module 2, a data analysis module 3, an information management module 4, a database 5 and an intelligent terminal 6, wherein the output end of the cloud platform 1 is respectively connected with the input ends of the data acquisition module 2, the data analysis module 3, the information management module 4, the database 5 and the intelligent terminal 6, and the input end of the cloud platform 1 is respectively connected with the output ends of the data acquisition module 2, the data analysis module 3, the information management module 4, the database 5 and the intelligent terminal 6; the cloud platform 1 is used for integrally and comprehensively controlling the system, the data acquisition module 2 is used for acquiring user retrieval information and information checking time and times of users, the data analysis module 3 is used for extracting key words and information and carrying out modeling processing, the information management module 4 is used for recommending, locking and unlocking the information, and the database 5 is used for storing and referring system data; the intelligent terminal 6 is used for displaying, setting and adjusting system data; the cloud platform 1 includes: the system comprises a central processing unit 7 and an information receiving and transmitting unit 8, wherein the central processing unit 7 performs comprehensive analysis processing on data, and the information receiving and transmitting unit 8 performs receiving and transmitting processing on the data information; the data acquisition module 2 includes: a retrieval acquisition unit 9, a time acquisition unit 10 and a frequency acquisition unit 11; the search acquisition unit 9 acquires search data input by a user, the time acquisition unit 10 is used for acquiring the stay watching time of the user in the existing information activity information, and the frequency acquisition unit 11 is used for acquiring the repeated watching times of the same kind of information activity information; the data analysis module 3 includes: a keyword extraction unit 12, an information extraction unit 13, and a model modeling unit 14; the keyword extraction unit 12 analyzes and extracts keywords of the information, the information extraction unit 13 extracts the information according to the information keywords, and the model modeling unit 14 builds an information recommendation model according to information recommendation data; the information management module 4 includes: an information recommending unit 15, an information locking unit 16, an information unlocking unit 17; the information recommending unit 15 recommends information, the information locking unit 16 locks and pushes information, and the information unlocking unit 17 unlocks and pushes information;
the database 5 comprises a storage unit 18, wherein the storage unit 18 comprises a local memory and a cloud memory;
the intelligent terminal 6 comprises an input unit 19 and a display unit 20, wherein the input unit 19 is used for inputting, setting and adjusting system data by a user, and the display unit 20 is used for displaying the system data;
the invention also provides a use method of the information activity information recommendation system under the big data situation, which comprises the following steps:
s1, starting a system through the intelligent terminal 6, acquiring search words of user search information by the data acquisition module 2, recommending information activity information according to the user search words, and acquiring data by the data acquisition module 2 in the database 5, wherein the historical stay watching time A of the user in the existing information activity information with the same key word information is acquired i Historical repeat viewing times B of identical keyword information activity information i The method comprises the steps of carrying out a first treatment on the surface of the Historical stay viewing time C for collecting approximate keyword information activity information i Historical repeat viewing count D of approximate keyword information activity information i ；
S2, the data analysis module 3 extracts keywords of the activity information, retrieves and extracts information in the database 5 according to the keywords and approximate or synonymous sentences of the keywords, determines the same keyword information activity information and approximate keyword information activity information, establishes an information recommendation model according to the front and back data information, and comprises the following steps: the number of pushing same keyword information activity information is E, G, while the number of pushing approximate keyword information activity information is F, H;
s3, when the user checks the search information, the information management module 4 pushes the same keyword information activity information to be E according to the user search data, and pushes the approximate keyword information activity information to be F;
T i for the average time spent for historically viewing the corresponding information activity information, n is the number of historically viewing the corresponding information activity information, t i For the average time spent on historically viewing the corresponding information activity information, m is the number of historically viewing the corresponding information activity information, and X is the total number of information activity information that can be displayed by the current search detection interface;
s4, when the user exits from checking the search information and checks the information under the condition of no other search tasks, entering an information locking state: pushing the same keyword information activity information to be G according to the user retrieval data, and pushing the approximate keyword information activity information to be H;
G＝E*(z*0.1)；
j is more than or equal to 1 and less than 4; j is the watching quantity of the information activity information of the same keyword information of the current interface;
H＝F*(y*0.1)；
k is more than or equal to 1 and less than 4; k is the watching quantity of the current interface approximate keyword information activity information;
when j is more than or equal to 4, unlocking the same keyword information lock, and pushing the same keyword information activity information to be E;
when k is more than or equal to 4, unlocking the approximate keyword information lock, and pushing the approximate keyword information activity information to be F;
after the user completely exits the information activity information application, and then enters the application later, according to the recommended information activity information of the earlier search keywords, the recommended number of the information activity information of the corresponding keywords is P, and the recommended number of the information activity information of the corresponding similar keywords is Q; x is the total number of information activity information which can be displayed by the current search detection interface;
s5, data in the system are collected in the cloud platform 1, the data in the system are stored in the database 5 in real time, a user can input the data through the intelligent terminal 6, and the user' S own preference and habit are input, set and corrected;
in the working movement process of the system, the data is updated in real time and the calculation formula is supplemented in real time.
The invention solves the problem that the existing information activity information recommendation system based on big data situation often pushes a large amount of information activity information aiming at user retrieval information; after the user finishes searching, whether the client still needs the information or not, the activity information is still recommended to the user, and the recommendation accuracy is poor.
The working principle of the invention is as follows:
referring to the attached figure 1 of the specification, the invention can acquire input search data in real time through user search data, acquire the stay watching time of the user in the existing information activity information in real time and the repeated watching times of the information activity information of the same kind by arranging the data acquisition module 2, the data analysis module 3, the information management module 4 and the database 5; extracting keywords of the activity information, and pushing the same keyword information activity information quantity and similar keyword information activity information quantity according to matching of the keywords and similar or synonymous words and sentences of the keywords; analyzing and judging the number of the follow-up information activity information recommendations according to the stay viewing time of the user on the information and the viewing times of the information activity information, and adjusting the number of the information activity information recommendations in real time; after searching and searching is interrupted, the information is in a locked state, the recommended quantity of similar activity information is directly and greatly reduced, meanwhile, the recommended quantity is adjusted in real time according to the follow-up searching data of a user, and when the searching quantity reaches a critical point, the locked state is released; meanwhile, determining the information quantity of recommended activities according to the watching habit of the user; when the user completely exits the information activity information application and subsequently reenters the application, the information quantity of the information activity of the corresponding keyword and the information pushing quantity of the information activity of the corresponding similar keyword are automatically recommended according to the information of the recommended information activity of the previous search keyword.
It is noted that relational terms such as first and second, and the like are used solely to distinguish one entity or action from another entity or action without necessarily requiring or implying any actual such relationship or order between such entities or actions. Moreover, the terms "comprises," "comprising," or any other variation thereof, are intended to cover a non-exclusive inclusion, such that a process, method, article, or apparatus that comprises a list of elements does not include only those elements but may include other elements not expressly listed or inherent to such process, method, article, or apparatus.
Finally, it should be noted that: the foregoing description is only a preferred embodiment of the present invention, and the present invention is not limited thereto, but it is to be understood that modifications and equivalents of some of the technical features described in the foregoing embodiments may be made by those skilled in the art, although the present invention has been described in detail with reference to the foregoing embodiments. Any modification, equivalent replacement, improvement, etc. made within the spirit and principle of the present invention should be included in the protection scope of the present invention.
Claims (9)
1. The utility model provides an information activity information recommendation system under big data situation, includes cloud platform (1), data acquisition module (2), data analysis module (3), information management module (4), database (5) and intelligent terminal (6), its characterized in that: the output end of the cloud platform (1) is respectively connected with the input ends of the data acquisition module (2), the data analysis module (3), the information management module (4), the database (5) and the intelligent terminal (6), and the input end of the cloud platform (1) is respectively connected with the output ends of the data acquisition module (2), the data analysis module (3), the information management module (4), the database (5) and the intelligent terminal (6); the cloud platform (1) is used for integrally and comprehensively controlling the system, the data acquisition module (2) is used for acquiring user retrieval information and information checking time and times of users, the data analysis module (3) is used for extracting keywords and information and carrying out modeling processing, the information management module (4) is used for recommending, locking and unlocking the information, and the database (5) is used for storing and referring system data; the intelligent terminal (6) is used for displaying, setting and adjusting system data; the application method of the information activity information recommendation system under the condition of big data comprises the following steps:
s1, starting a system through the intelligent terminal (6), collecting search words of user search information by the data collection module (2), recommending information activity information according to the user search words, and collecting data by the data collection module (2) in a database (5), wherein historical stay viewing time A of a user in the existing information activity information of the same key word is collected i Historical repeat viewing times B of identical keyword information activity information i The method comprises the steps of carrying out a first treatment on the surface of the Historical stay viewing time C for collecting approximate keyword information activity information i Historical repeat viewing count D of approximate keyword information activity information i ；
S2, extracting keywords of the activity information by the data analysis module (3), searching and extracting information in the database (5) according to the keywords and the approximate or synonymous sentences of the keywords, determining the same keyword information activity information and the approximate keyword information activity information, and establishing an information recommendation model according to the front and back data information, wherein the model comprises the following steps: the number of pushing same keyword information activity information is E, G, while the number of pushing approximate keyword information activity information is F, H;
s3, when the user checks the search information, pushing the same keyword information activity information to be E according to the user search data, and pushing the approximate keyword information activity information to be F;
T i for the average time spent for historically viewing the corresponding information activity information, n is the number of historically viewing the corresponding information activity information, t i For the average time spent on historically viewing the corresponding information activity information, m is the number of historically viewing the corresponding information activity information, and X is the total number of information activity information that can be displayed by the current search detection interface;
s4, when the user exits from checking the search information and checks the information under the condition of no other search tasks, entering an information locking state: pushing the same keyword information activity information to be G according to the user retrieval data, and pushing the approximate keyword information activity information to be H;
G＝E*(z*0.1)；
j is more than or equal to 1 and less than 4; j is the watching quantity of the information activity information of the same keyword information of the current interface;
H＝F*(y*0.1)；
k is more than or equal to 1 and less than 4; k is the watching quantity of the current interface approximate keyword information activity information;
when j is more than or equal to 4, unlocking the same keyword information lock, and pushing the same keyword information activity information to be E;
when k is more than or equal to 4, unlocking the approximate keyword information lock, and pushing the approximate keyword information activity information to be F;
s5, data in the system are collected in the cloud platform (1), the data in the system are stored in the database (5) in real time, and a user can input the data through the intelligent terminal (6) to input setting and correcting the user' S own preference and habit.
2. The information recommendation system for information activities in a big data scenario of claim 1, wherein: the cloud platform (1) comprises: the system comprises a central processing unit (7) and an information receiving and transmitting unit (8), wherein the central processing unit (7) performs comprehensive analysis processing on data, and the information receiving and transmitting unit (8) performs receiving and transmitting processing on the data information.
3. The information recommendation system for information activities in a big data scenario of claim 1, wherein: the data acquisition module (2) comprises: a retrieval acquisition unit (9), a time acquisition unit (10) and a frequency acquisition unit (11); the search acquisition unit (9) is used for acquiring search data input by a user, the time acquisition unit (10) is used for acquiring the stay watching time of the user in the existing information activity information, and the frequency acquisition unit (11) is used for acquiring the repeated watching times of the same kind of information activity information.
4. The information recommendation system for information activities in a big data scenario of claim 1, wherein: the data analysis module (3) comprises: a keyword extraction unit (12), an information extraction unit (13), and a model modeling unit (14); the keyword extraction unit (12) analyzes and extracts keywords of the information, the information extraction unit (13) extracts the information according to the information keywords, and the model modeling unit (14) builds an information recommendation model according to information recommendation data.
5. The information recommendation system for information activities in a big data scenario of claim 1, wherein: the information management module (4) includes: an information recommending unit (15), an information locking unit (16), an information unlocking unit (17); the information recommending unit (15) recommends information, the information locking unit (16) locks and pushes information, and the information unlocking unit (17) unlocks and pushes information.
6. The information recommendation system for information activities in a big data scenario of claim 1, wherein: the database (5) comprises a storage unit (18), and the storage unit (18) comprises a local memory and a cloud memory.
7. The information recommendation system for information activities in a big data scenario of claim 1, wherein: the intelligent terminal (6) comprises an input unit (19) and a display unit (20), wherein the input unit (19) is used for inputting, setting and adjusting system data by a user, and the display unit (20) is used for displaying the system data.
8. The information recommendation system for information activities in a big data scenario of claim 1, wherein: in the working movement process of the system, the data is updated in real time and the calculation formula is supplemented in real time.
9. The information recommendation system for information activities in a big data scenario of claim 1, wherein: after the user completely exits the information activity information application, and then enters the application later, according to the recommended information activity information of the earlier search keywords, the recommended number of the information activity information of the corresponding keywords is P, and the recommended number of the information activity information of the corresponding similar keywords is Q; x is the total number of information activity information which can be displayed by the current search detection interface;
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| CN106971006A (en) * | 2017-04-27 | 2017-07-21 | 暴风集团股份有限公司 | The personalized push method and system of a kind of competitive sports information |
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