A cross-domain collaborative filtering method and system

A collaborative filtering and cross-domain technology, applied in the field of cross-domain collaborative filtering methods and systems, can solve problems such as data set imbalance in recommendation systems, and achieve the effect of overcoming skewed distribution problems, reducing sparsity, and solving data set imbalances.

Active Publication Date: 2019-03-08
QINGDAO UNIV OF SCI & TECH
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AI Technical Summary

Problems solved by technology

[0005] This application provides a cross-domain collaborative filtering method and system to solve the technical problem of unbalanced data sets in existing recommendation systems

Method used

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  • A cross-domain collaborative filtering method and system
  • A cross-domain collaborative filtering method and system
  • A cross-domain collaborative filtering method and system

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Embodiment Construction

[0023] The specific implementation manners of the present application will be described in further detail below in conjunction with the accompanying drawings.

[0024] The cross-domain collaborative filtering method proposed in this application aims to convert the user-item scoring matrix of the target domain into a training sample set, then expand it with auxiliary domain data to solve the problem of data sparsity in the target domain, and then perform different training samples after expansion. The training of the balanced classifier uses the unbalanced classifier to predict the missing items in the target domain, and then obtains the recommended data, which solves the sparse and unbalanced problems of the existing recommendation system data sets. Specifically include the following steps:

[0025] Step S11: Convert the user item rating data into a training sample set for the classification algorithm.

[0026] In the embodiment of this application, it is assumed that the tar...

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Abstract

The invention discloses a cross-domain collaborative filtering method. After the user item scoring data is converted into a training sample set, the user item scoring matrix of each auxiliary domain is processed with the Funk-SVD decomposition to obtain a user potential vector, a first set of extended training samples is then obtained by expanding the set of training samples by using the user potential vector, adding item feature information to expand the first set of extended training samples to obtain a second set of extended training samples, training an unbalanced classifier using the second set of extended training samples, and finally predicting missing data of the user item scoring data based on the unbalanced classifier and generating a recommendation. The problem of data sparsityin the target domain is solved by using auxiliary domain data, and then the unbalanced classifier is trained to predict the missing items in the target domain, and the recommendation data are obtainedto solve the problem of data sparsity and unbalance in the existing recommendation system.

Description

technical field [0001] The invention belongs to the technical field of information recommendation, and in particular relates to a cross-domain collaborative filtering method and system. Background technique [0002] The rapid growth of Internet information requires effective intelligent information agents that can filter out all available information and find the most valuable information for users. [0003] In recent years, recommendation systems have been widely used in e-commerce networks and online social media. At present, the main recommendation methods are divided into: content-based recommendation, collaborative filtering-based recommendation, association rule-based recommendation, utility-based recommendation, knowledge-based recommendation, Combination recommendation, etc. Among them, the recommendation based on collaborative filtering is the most successful strategy in the recommendation method. The basic idea is that the user is likely to like the resource that i...

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Application Information

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Patent Type & Authority Applications(China)
IPC IPC(8): G06F16/9535G06F16/35G06Q30/06
CPCG06Q30/0631
Inventor 于旭付裕徐凌伟杜军威巩敦卫
Owner QINGDAO UNIV OF SCI & TECH
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