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University library-oriented books personalized recommendation method and system

A recommendation method and library technology, applied in the field of machine learning, can solve problems such as complex data storage and search, sparse scoring matrix, and poor scalability

Active Publication Date: 2016-12-07
HUAZHONG UNIV OF SCI & TECH
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  • Abstract
  • Description
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  • Application Information

AI Technical Summary

Problems solved by technology

[0004] Aiming at the above deficiencies or improvement needs of the prior art, the present invention provides a method and system for recommending books in university libraries. There are problems of poor scalability, extremely sparse scoring matrix and "cold start" for new users in the book recommendation algorithm, and improve the quality of book recommendation

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  • University library-oriented books personalized recommendation method and system
  • University library-oriented books personalized recommendation method and system
  • University library-oriented books personalized recommendation method and system

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Embodiment Construction

[0049] 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 and embodiments. It should be understood that the specific embodiments described here are only used to explain the present invention, not to limit the present invention. In addition, the technical features involved in the various embodiments of the present invention described below can be combined with each other as long as they do not constitute a conflict with each other.

[0050] Such as figure 1 As shown, the present invention faces the book personalized recommendation method of university library and comprises the following steps:

[0051] (1) Perform data cleaning on the source data of the university library (mainly including operations such as deleting erroneous data, irrelevant redundant information, and processing incomplete data) to extract the metadata, a...

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Abstract

The invention discloses a university library-oriented books personalized recommendation method, and solves the problems of poor large-scale data storage and query, extendibility and recommendation effect in an existing books recommendation algorithm of a university library. According to the basic thought, the method comprises the following steps of firstly, building a graph model by taking readers, books and the like in the library as nodes; secondly, converting operation log files of the readers into a reader-books category preference matrix, calculating similarity between the readers by the reader-books category preference matrix and a reader personal information matrix, and establishing an associated graph spectrum by taking operations and mined information as edges; thirdly, by combining the associated graph spectrum with spectral clustering, proposing a new books personalized recommendation model, and performing calculation to obtain class cluster distribution about the readers; and finally, when books recommendation needs to be carried out, calculating a recommended books list according to a collaborative filtering algorithm in a class cluster corresponding to a reader.

Description

technical field [0001] The invention belongs to the technical field of machine learning, and more specifically relates to a method and system for personalized recommendation of books oriented to university libraries. Background technique [0002] In the daily study and life of various colleges and universities, libraries play an important role both among students and among teachers. Students and teachers cannot do without the help of libraries to find documents or learning materials. However, with the explosive growth of modern information, the number of books in university libraries has exceeded one million. Although modern technologies such as digital libraries have alleviated this problem to a certain extent, readers still need to search through keywords. Browsing and screening among many search results, and in many cases, readers do not know what their target books are. Facing such problems, the personalized book recommendation system was born. [0003] The current rese...

Claims

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Application Information

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Patent Type & Authority Applications(China)
IPC IPC(8): G06F17/30
CPCG06F16/90335G06F16/907
Inventor 周可李春花吕丹阳
Owner HUAZHONG UNIV OF SCI & TECH
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