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Book recommendation method and system based on matrix decomposition collaborative filtering algorithm

A collaborative filtering algorithm and matrix decomposition technology, applied in computing, computing models, special data processing applications, etc., can solve problems such as weak scalability, achieve the effect of overcoming data sparseness and weak scalability, and improving accuracy

Active Publication Date: 2018-09-07
宁夏三得教育科技有限公司
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AI Technical Summary

Problems solved by technology

[0005] Personally recommend books that may be of interest to different users, overcome the problems of data sparsity and weak scalability in memory-based methods, and improve the accuracy of recommendation algorithms

Method used

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  • Book recommendation method and system based on matrix decomposition collaborative filtering algorithm
  • Book recommendation method and system based on matrix decomposition collaborative filtering algorithm
  • Book recommendation method and system based on matrix decomposition collaborative filtering algorithm

Examples

Experimental program
Comparison scheme
Effect test

Embodiment

[0098] The following uses a dataset of 129,334 user book rating records, involving a total of 265 books and 1968 users. Some of the book rating information of user cytun is shown in Table 1 and Table 2.

[0099] Table 1

[0100]

[0101]

[0102]

[0103] Table 2

[0104]

[0105] In the operation process of this algorithm, user-behavior data needs to be processed into a user-book rating matrix, and then the user rating matrix is ​​decomposed into a user feature matrix and a book feature matrix, and the above two matrices are continuously updated through the gradient descent method. Until the cost function is minimized, use the obtained optimal feature matrix to predict the ratings of candidate recommended items. Part of the data of the user rating matrix R in this example is as follows:

[0106]

[0107] If the user has not rated the book, this is set to 0 in the matrix. The third row of the matrix is ​​the historical rating data of user cytun, and the fourt...

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Abstract

The invention discloses a book recommendation method and system based on a matrix decomposition collaborative filtering algorithm. The invention realizes the book recommendation method based on the matrix decomposition collaborative filtering algorithm. By use of the method, a recommendation technology is applied to the book recommendation system so as to realize a purpose that other books in which a reading fan is interested are recommended to the reading fan in a personalized way, and time for the reading fan to find books in which the reading fan is interested from mass image information isshortened. A recommendation algorithm applied by the method is the book recommendation method based on the collaborative filtering algorithm, the collaborative filtering algorithm based on the matrixdecomposition is specifically used, the collaborative filtering algorithm based on the matrix decomposition takes user scores as feature vectors, and the score of a book is predicted through the training of a regression model. By use of the algorithm, the problems of data sparsity, weak expandability and the like in a method based on a memory can be effectively solved, and meanwhile, the accuracyof the recommendation algorithm can be improved.

Description

technical field [0001] The invention belongs to the technical field of book recommendation, and relates to a book recommendation method and system based on a matrix decomposition collaborative filtering algorithm. Background technique [0002] A recommender system is a means to help match information with users. Unlike search engines, the recommendation system does not require users to enter additional keywords. It can actively mine users' interests and hobbies based on the user's past behavior records, help users discover potential points of interest, and recommend related products or information to user. Because it is recommended according to the characteristics of each user, it can meet individual requirements, recommend products that meet their individual needs for different users, and make information more accurately displayed in front of users. At the same time, it is not so Rely on information actively entered by the user to filter information. [0003] In the fiel...

Claims

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Application Information

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Patent Type & Authority Applications(China)
IPC IPC(8): G06F17/30G06N99/00
Inventor 栾飞李媛鸣陈梦瑶石冰洁王川刘二宝祝晓雪高婧
Owner 宁夏三得教育科技有限公司
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