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A Book Recommendation Method Based on Adaptive Clustering

An adaptive clustering and recommendation method technology, applied in the field of network communication, can solve the problems of users recommending long-tail books and unpopular long-tail books, and achieve the effect of increasing the number of book visits and increasing the overall income

Inactive Publication Date: 2016-08-10
EB INFORMATION TECH
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  • Summary
  • Abstract
  • Description
  • Claims
  • Application Information

AI Technical Summary

Problems solved by technology

However, because long-tail books are relatively unpopular, it is difficult for ordinary collaborative filtering and SlopeOne algorithms to recommend long-tail books that meet their personalization.

Method used

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  • A Book Recommendation Method Based on Adaptive Clustering
  • A Book Recommendation Method Based on Adaptive Clustering
  • A Book Recommendation Method Based on Adaptive Clustering

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Embodiment Construction

[0018] In order to make the object, technical solution and advantages of the present invention clearer, the present invention will be further described in detail below in conjunction with the accompanying drawings.

[0019] Such as figure 1 Shown, a kind of book recommendation method based on self-adaptive clustering of the present invention includes:

[0020] Step 1. Divide the books into several book clusters according to the access data of the books;

[0021] Step 2. Calculate the average book score of each book cluster according to the ratings of all books in the book cluster;

[0022] Step 3. According to the difference of the average score of books in different book clusters, the number of common users of different book clusters, and the average value of the user's ratings on the read books in each book cluster, calculate the user's score for each book cluster. rating of the class;

[0023] Step 4. According to the difference between the score of each book and the ave...

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Abstract

The invention discloses a book recommendation method based on self-adaption clustering. The method comprises the following steps:1, respectively dividing books into a plurality of book clusters according to access datum of books; 2, calculating a book average score of each book cluster according to scores of all books in the book cluster; 3, calculating the scores from users to each book according to a difference value of the book average scores of different book clusters, a common user number of different book clusters and an average value of the scores from users to the read books in each book cluster; and 4, calculating the scores from users to the unread books in each book cluster according to the difference value of the score of each book and the book average score of the book cluster to which the book is belonged to, and the scores from users to each book cluster; and recommending books to users according to the scores. The book recommendation method belongs to the technical field of network communication, and can recommend more personalized long tail books to users.

Description

technical field [0001] The invention relates to a method for recommending books based on self-adaptive clustering, which belongs to the technical field of network communication. Background technique [0002] As mobile reading develops and is gradually accepted by users, how to accurately grasp users' reading preferences and quickly push information that meets users' preferences to users in a straight-line distance is particularly important. [0003] Although theoretically all books will be purchased, the purchase and recommendation of books will be biased towards popular books. For popular books, users can access them in many other ways (such as rankings, etc.), while long-tail books are difficult to be recommended to users due to their relatively small number of orders and visits. At the same time, various platforms will compete with each other for the prices of popular books due to price wars and other reasons, which will gradually reduce the profits of popular books. Th...

Claims

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Application Information

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Patent Type & Authority Patents(China)
IPC IPC(8): G06F17/30G06Q30/02
Inventor 廖建新李曲刘红明崔晓茹赵贝尔
Owner EB INFORMATION TECH