CN112612962A - Personalized recommended content access duplication elimination management method - Google Patents
Personalized recommended content access duplication elimination management method Download PDFInfo
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- 238000007726 management method Methods 0.000 title claims abstract description 18
- 230000008030 elimination Effects 0.000 title description 5
- 238000003379 elimination reaction Methods 0.000 title description 5
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- 230000008707 rearrangement Effects 0.000 claims abstract description 7
- 238000000034 method Methods 0.000 claims description 15
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- G06F16/90—Details of database functions independent of the retrieved data types
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- G06F16/00—Information retrieval; Database structures therefor; File system structures therefor
- G06F16/90—Details of database functions independent of the retrieved data types
- G06F16/95—Retrieval from the web
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Abstract
A personalized recommended content access and rearrangement management method comprises the steps of constructing a master pool, adding new content to a designated position of the master pool in real time, constructing a user pool in redis each time a user starts an application, acquiring a page of list data, recording browsing behaviors of the user on a system through the start of the application, repeating the first step, the second step, the third step and the fourth step if a personalized recommended cache pool of the user is overdue, constructing the master pool, adding the new content to the inside of the master pool in real time whenever, constructing a user pool in the redis when the user starts the application, wherein the user pools can be multiple, the data acquisition is efficient because the acquired list data are all taken from the redis, and the redis is a high-performance and high-concurrency-supporting server, and different unviewed contents can be recommended to the user efficiently according to different recommendation algorithms, the efficiency and the practical effect of recommending the content are improved.
Description
Technical Field
The invention relates to the technical field of content access duplication elimination management methods, in particular to a personalized recommended content access duplication elimination management method.
Background
In the information society of today, personalized recommendation systems are inseparable from our lives. When reading news information, shopping online, listening to music, watching videos, we see various "recommendation" lists in the form of "guessing you like", "goods you may be interested in", "users who are similar to your interests are still watching", etc. Personalized recommendation thousands of people recommend information or goods of real interest to a user by deeply analyzing and mining the behavior data of the user. For individuals, personalized recommendation can help users to solve the problem of unsuitability when facing various services such as rich and various commodities, movies, songs, videos and the like. For enterprises, personalized recommendation can not only provide excellent user physical examination and meet the information requirements of the users, but also help the enterprises to mine infinite business opportunities contained in the user physical examination, and effectively improve the click rate, the payment rate and the secondary purchase rate of the users.
However, in the existing personalized recommended content access method, the redis storage capacity is too large-each user has respective cache, when the user capacity is large, the data capacity of the redis storage is too large, when the storage capacity is large, one redis server is not enough, the problem of data consistency of the redis server is solved by adopting a cluster mode, and when the device cache is constructed each time, more time is spent, and the practical rate is not high.
Disclosure of Invention
Technical problem to be solved
Aiming at the defects of the prior art, the invention provides a personalized recommended content access and rearrangement management method with high utilization rate.
(II) technical scheme
In order to achieve the purpose, the invention provides the following technical scheme: a personalized recommended content access and rearrangement management method comprises the following steps:
the method comprises the following steps: and constructing a total pool, and adding the new content to the specified position of the total pool in real time.
Step two: each time a user starts an application, a pool of users is built within the redis.
Step three: one page list data is acquired.
Step four: and recording the browsing behavior of the user on the system by starting the application.
Step five: and if the user personalized recommended cache pool is expired, repeating the first step, the second step, the third step and the fourth step.
In order to improve the performance of the personalized recommendation cache, the invention has the improvement that data is obtained from the total pool, and the personalized recommendation total data is calculated through a recommendation algorithm, wherein the recommendation algorithm can be an algorithm for intelligently analyzing the favorite and interesting things of the user or an algorithm for sorting according to the weight of data which is pushed to the user by application.
In order to realize better pushing, the invention improves that personalized recommendation, pushed and read are arranged in the user pool.
In order to improve the pushing efficiency, the invention improves that the personalized recommendation is total personalized recommendation data-pushed-read, the personalized recommendation data is stored in redis, the cache expiration time is set to be 30 minutes, and the cache expiration time can be set according to specific conditions.
In order to ensure that the repeated pushing is avoided, the invention has the improvement that the most front page of data is obtained in the personalized recommendation cache of the user, and the page of data is added to the pushed end after being taken out.
In order to better record the browsing behavior of the user on the system, the invention improves that the browsing behavior of the user on the system can be recorded into A, B:
the A line is as follows: 1. the method comprises the steps that a user calls an interface for acquiring a page of data, the interface responds to return a page of data, the page of data is displayed in a list of the user, 2, the page of data needs to be removed from a personalized recommended cache of the user while the page of data is acquired, and then the page of data is added at the tail end of a pushed cache of the user.
B, behavior: 1. when a user clicks a certain piece of data to enter a detail page 2, the data needs to be removed from the pushed cache and then added to the end of the read cache while entering the detail page.
(III) advantageous effects
Compared with the prior art, the invention provides a personalized recommended content access and duplication elimination management method, which has the following beneficial effects:
the personalized recommended content access and rearrangement management method constructs a total pool, and adds the total pool to the interior of the total pool in real time when new content exists, and when a user starts an application, a user pool can be constructed in redis, wherein the user pool can be a plurality of user pools, because the acquired list data are all acquired from the redis, and the redis is a high-performance and high-concurrency-supporting server, the data acquisition is very efficient, and because the personalized recommendation can be carried out according to different recommendation algorithms, different unviewed contents can be recommended to the user efficiently, and the content recommendation efficiency and the practical effect are improved.
Drawings
FIG. 1 is a schematic diagram of a main flow structure of the present invention;
FIG. 2 is a schematic diagram of a personalized recommendation data calculation structure of FIG. 1 according to the present invention;
FIG. 3 is a schematic view of the flow structure of FIG. 1 at 2 according to the present invention;
FIG. 4 is a schematic view of the flow structure of FIG. 1 at 2 according to the present invention;
Detailed Description
The technical solutions in the embodiments of the present invention will be clearly and completely described below with reference to the drawings in the embodiments of the present invention, and it is obvious that the described embodiments are only a part of the embodiments of the present invention, and not all of the embodiments. All other embodiments, which can be derived by a person skilled in the art from the embodiments given herein without making any creative effort, shall fall within the protection scope of the present invention.
Referring to fig. 1-4, a personalized recommended content access deduplication management method includes the following steps:
the method comprises the following steps: and constructing a total pool, and adding the new content to the specified position of the total pool in real time.
Step two: each time a user starts an application, a pool of users is built within the redis.
Step three: one page list data is acquired.
Step four: and recording the browsing behavior of the user on the system by starting the application.
Step five: and if the user personalized recommended cache pool is expired, repeating the first step, the second step, the third step and the fourth step.
In order to improve the performance of the personalized recommendation cache, the invention has the improvement that data is obtained from the total pool, and the personalized recommendation total data is calculated through a recommendation algorithm, wherein the recommendation algorithm can be an algorithm for intelligently analyzing the favorite and interesting things of the user or an algorithm for sorting according to the weight of data which is pushed to the user by application.
In order to realize better pushing, the invention improves that personalized recommendation, pushed and read are arranged in the user pool.
In order to improve the pushing efficiency, the invention improves that the personalized recommendation is total personalized recommendation data-pushed-read, the personalized recommendation data is stored in redis, the cache expiration time is set to be 30 minutes, and the cache expiration time can be set according to specific conditions.
In order to ensure that the repeated pushing is avoided, the invention has the improvement that the most front page of data is obtained in the personalized recommendation cache of the user, and the page of data is added to the pushed end after being taken out.
In order to better record the browsing behavior of the user on the system, the invention improves that the browsing behavior of the user on the system can be recorded into A, B:
the A line is as follows: 1. the method comprises the steps that a user calls an interface for acquiring a page of data, the interface responds to return a page of data, the page of data is displayed in a list of the user, 2, the page of data needs to be removed from a personalized recommended cache of the user while the page of data is acquired, and then the page of data is added at the tail end of a pushed cache of the user.
B, behavior: 1. when a user clicks a certain piece of data to enter a detail page 2, the data needs to be removed from the pushed cache and then added to the end of the read cache while entering the detail page.
In summary, the working principle and working process of the personalized recommended content access and rearrangement management method are that, when the personalized recommended content access and rearrangement management method is used, a total pool is firstly constructed, when new content exists, all data are stored in the total pool in real time to form the total pool, when a user starts application, a user pool is constructed in the redis, the user pool can be a plurality of user pools, the user refers to a certain user who obtains list data in a system, the user pool comprises personalized recommendation, pushed and read, the personalized recommendation is total personalized recommendation data-pushed-read, the personalized recommendation data can be stored in the redis, the cache expiration time is set to be 30 minutes, the cache expiration time can be set by self according to specific conditions, the personalized recommendation total data can be calculated through a recommendation algorithm, the recommendation algorithm can be an algorithm for intelligently analyzing user preferences and interesting things, or an algorithm for sorting according to data weights which are applied and are expected to be pushed to the user, different contents which are not browsed by the user can be efficiently recommended according to the two different recommendation algorithms, the recommended contents are prevented from being repeated, and when browsing lines of the user on the system are recorded, the behaviors A are divided into A, B: 1. the method comprises the following steps that a user calls an interface for acquiring a page of data, the interface responds to return a page of data, the page of data is displayed in a list of the user, 2, when the page of data is acquired, the page of data needs to be removed from a personalized recommended cache of the user, then the page of data is added at the end of a pushed cache of the user, and B, the actions are as follows: 1. when a user clicks a certain piece of data, the data is entered into a detail page, 2, the data needs to be removed from a pushed cache and then added to the end of a read cache, so that the data of a list is not repeated and is the personalized new data which is not browsed by the user, the efficiency of recommending content is further improved, when a personalized recommendation cache pool in a user pool is overdue, the first step, the second step, the third step and the fourth step are repeated, and the total personalized recommendation data always ensures that the recommended content is the new content.
Although embodiments of the present invention have been shown and described, it will be appreciated by those skilled in the art that changes, modifications, substitutions and alterations can be made in these embodiments without departing from the principles and spirit of the invention, the scope of which is defined in the appended claims and their equivalents.
Claims (6)
1. A personalized recommended content access and rearrangement management method is characterized by comprising the following steps: the method comprises the following steps:
the method comprises the following steps: constructing a total pool, and adding new contents to the specified position of the total pool in real time;
step two: when a user starts an application each time, a user pool is constructed in the redis;
step three: acquiring list data of a page;
step four: recording the browsing behavior of a user on the system by starting an application;
step five: and if the user personalized recommended cache pool is expired, repeating the first step, the second step, the third step and the fourth step.
2. The method of claim 1, wherein the personalized recommended content access ranking management method comprises: and acquiring data from the total pool, and calculating personalized recommended total data through a recommendation algorithm, wherein the recommendation algorithm is an algorithm for intelligently analyzing user preference and interested things, or an algorithm for sorting according to the weight of data which is applied and is expected to be pushed to a user.
3. The method of claim 1, wherein the personalized recommended content access ranking management method comprises: the user pool is internally provided with personalized recommendation, pushed and read.
4. The method of claim 1, wherein the personalized recommended content access ranking management method comprises: and the personalized recommendation is total personalized recommendation data-pushed-read, the personalized recommendation data is stored in redis, and the cache expiration time is set to be 30 minutes.
5. The method of claim 1, wherein the personalized recommended content access ranking management method comprises: and acquiring the most front page of data in the user personalized recommendation cache, and adding the page of data to the pushed end after the data is taken out.
6. The method of claim 1, wherein the personalized recommended content access ranking management method comprises: recording the browsing lines of a user on the system can be divided into A, B two behaviors:
the A line is as follows: 1. the method comprises the steps that a user calls an interface for acquiring a page of data, the interface responds to return a page of data, the page of data is displayed in a list of the user, 2, the page of data needs to be removed from a personalized recommended cache of the user while the page of data is acquired, and then the page of data is added at the tail end of a pushed cache of the user.
B, behavior: 1. when a user clicks a certain piece of data to enter a detail page 2, the data needs to be removed from the pushed cache and then added to the end of the read cache while entering the detail page.
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Cited By (1)
| Publication number | Priority date | Publication date | Assignee | Title |
|---|---|---|---|---|
| CN114169785A (en) * | 2021-12-13 | 2022-03-11 | 金螳螂家装电子商务（苏州）有限公司 | Home decoration content accurate pushing method |
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| US20180322206A1 (en) * | 2017-05-05 | 2018-11-08 | Microsoft Technology Licensing, Llc | Personalized user-categorized recommendations |
| CN110633760A (en) * | 2019-09-25 | 2019-12-31 | 北京酷我科技有限公司 | Recommendation system integration strategy and recommendation system |
| CN111949890A (en) * | 2020-09-27 | 2020-11-17 | 平安科技（深圳）有限公司 | Data recommendation method, equipment, server and storage medium based on medical field |
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2020
- 2020-12-28 CN CN202011578381.3A patent/CN112612962A/en active Pending
Patent Citations (5)
| Publication number | Priority date | Publication date | Assignee | Title |
|---|---|---|---|---|
| CN105608117A (en) * | 2015-12-14 | 2016-05-25 | 微梦创科网络科技（中国）有限公司 | Information recommendation method and apparatus |
| CN106998274A (en) * | 2016-12-12 | 2017-08-01 | 深圳大宇无限科技有限公司 | Application message method for pushing and device |
| US20180322206A1 (en) * | 2017-05-05 | 2018-11-08 | Microsoft Technology Licensing, Llc | Personalized user-categorized recommendations |
| CN110633760A (en) * | 2019-09-25 | 2019-12-31 | 北京酷我科技有限公司 | Recommendation system integration strategy and recommendation system |
| CN111949890A (en) * | 2020-09-27 | 2020-11-17 | 平安科技（深圳）有限公司 | Data recommendation method, equipment, server and storage medium based on medical field |
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| CN114169785A (en) * | 2021-12-13 | 2022-03-11 | 金螳螂家装电子商务（苏州）有限公司 | Home decoration content accurate pushing method |
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Effective date of registration: 20220726 Address after: 361000 unit 02, floor 5, building B, Guojin Plaza, No. 506-508 Qianpu Road, Siming District, Xiamen City, Fujian Province Applicant after: Xiamen best material Digital Technology Co.,Ltd. Address before: 361026 room 304, 3rd floor, building 7, 66 HouXiang Road, Haicang District, Xiamen City, Fujian Province Applicant before: Xiamen best material information technology Co.,Ltd. |
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Application publication date: 20210406 |