Collaborative filtering recommendation method of theme based on viewpoint enhancement

A collaborative filtering recommendation and topic technology, applied in the information field, can solve the problems of poor recommendation effect and dispersion, and achieve the effect of accurate personalized recommendation and good robustness.

Inactive Publication Date: 2018-06-29
WUHAN UNIV
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Problems solved by technology

[0005] The purpose of the present invention is to transform the relationship between the user and the product to the relationship between the user and the product attribute surface by improving the granularity and accuracy of the product recomm

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  • Collaborative filtering recommendation method of theme based on viewpoint enhancement
  • Collaborative filtering recommendation method of theme based on viewpoint enhancement
  • Collaborative filtering recommendation method of theme based on viewpoint enhancement

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[0016] In order to facilitate the understanding and implementation of the present invention by those of ordinary skill in the art, the present invention will be further described in detail with reference to the accompanying drawings and embodiments. It should be understood that the implementation examples described here are only used to illustrate and explain the present invention, and are not intended to limit this invention.

[0017] Please see figure 1 with figure 2 , The present invention provides a method for topic collaborative filtering recommendation based on opinion enhancement, which is characterized in that it includes the following steps:

[0018] Step 1: Extract comment text attribute words based on the LDA topic model;

[0019] The present invention introduces the LDA topic model to extract attribute words. The LDA topic model can extract a series of topic units related to text semantics from large-scale texts. These topic units can better reflect the attribute inform...

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Abstract

The invention discloses a collaborative filtering recommendation method of a theme based on viewpoint enhancement. The method includes the steps that first, comment text attribute words are extractedbased on an LDA theme model; then, the similar attribute words are classified as one category by utilizing a word2vec model to calculate relations among the attribute words based on the attribute words extracted by the LDA; the attribute words with the same meanings are collected as an attribute surface; the sentiment polarity of comment texts is obtained through the analysis of attribute surfaceviewpoint enhancement; next, a scoring matrix is constructed according to the polarity of sentiment words and attribute words, and the similarity among users is calculated according to a scoring method and through a collaborative filtering algorithm; finally, goods with high scores in the matrix are recommended to other users according to a k-nearest neighbor algorithm. Experimental results show that the collaborative filtering recommendation method is excellent in F value extracted by attribute words and mean absolute error of recommendation.

Description

technical field [0001] The invention belongs to the field of information technology and relates to an information recommendation method, in particular to a new comment text-based personalized recommendation method which combines the advantages of collaborative filtering algorithm and content-based recommendation. Background technique [0002] The development of the Internet sharing information platform enables people all over the world to share their emotions or opinions with others through the Internet. However, the explosive growth of information makes it difficult for users to obtain information closely related to themselves. The recommendation system can provide users with the most needed information by utilizing the potential relationship between users and products, thus solving this problem better. The recommendation system is different from the earlier information system tools or technologies such as databases and search engines. It is a relatively new field. There ...

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Application Information

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IPC IPC(8): G06F17/30G06Q30/06
CPCG06F16/335G06F16/9535G06Q30/0631
Inventor 彭敏施洪亮胡刚
Owner WUHAN UNIV
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