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Sparse data preprocessing based collaborative filtering recommendation method

A collaborative filtering recommendation and sparse data technology, applied in the field of Internet information, can solve the problems of no-value and multiple-value, and achieve the effect of simple method, convenient data collection, and improved accuracy

Inactive Publication Date: 2016-02-24
NANJING UNIV OF POSTS & TELECOMM
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But again, using this method, there will be many and no majority values

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  • Sparse data preprocessing based collaborative filtering recommendation method
  • Sparse data preprocessing based collaborative filtering recommendation method
  • Sparse data preprocessing based collaborative filtering recommendation method

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[0034] The invention will be described in further detail below in conjunction with the accompanying drawings.

[0035] Such as figure 1 As shown, the present invention is a collaborative filtering recommendation method based on sparse data preprocessing. Since the KNN algorithm is a common algorithm in the collaborative filtering recommendation algorithm, the construction of the item feature attribute matrix, weight assignment, similarity calculation, and prediction filling value calculation of unrated items will be described in detail below.

[0036] The concrete implementation steps of the present invention comprise as follows:

[0037] Step 1: According to the data information of the item itself in the recommendation system, construct the item feature attribute matrix, where the row represents the item, the column represents the feature attribute, and the intersection value of the row and column is filled with 0 or 1, and 0 means that the item does not have this feature at...

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Abstract

The invention discloses a sparse data preprocessing based collaborative filtering recommendation method. The method is carried out based on information of a project; firstly, characteristic attribute information of the project is introduced, and different weights are allocated to each characteristic attribute; the similarity of the characteristic attributes among projects is calculated; the score on non-graded projects from users is predicted initially; then hybrid filling preprocessing is preformed on the non-graded projects in a spare data set to enable the sparse users and project data matrix to be fully saturated. The problems of low recommendation precision and low recommendation coverage caused by that the sparse data are not processed or fixed values are adopted for filling in the conventional method are effectively solved by the sparse data preprocessing based collaborative filtering recommendation method provided by the invention, so that the recommendation performance of a recommendation system based on the sparse data preprocessing based collaborative filtering recommendation method is well improved.

Description

technical field [0001] The invention relates to a collaborative filtering recommendation method based on sparse data preprocessing, which belongs to the field of Internet information technology. Background technique [0002] With the continuous development of the Internet and information technology, people have gradually entered the era of information surplus from the era of information scarcity. In this era, both information producers and information consumers are facing huge challenges. As information producers, how to make their information stand out and attract the attention of the majority of users is a very difficult thing. . As a consumer of information, how to find the information you are interested in from the massive amount of information is also a very complicated matter. Therefore, collaborative filtering recommendation has become one of the research hotspots of Internet information technology. [0003] The task of collaborative filtering recommendation is to ...

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Application Information

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Patent Type & Authority Applications(China)
IPC IPC(8): G06F17/30
CPCG06F16/9535
Inventor 陈宗言颜俊朱卫平
Owner NANJING UNIV OF POSTS & TELECOMM
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