SVMs Classification Based Two-side Cross Domain Collaborative Filtering by inferring intrinsic user and item features-Reference-Cited by-同舟云学术

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SVMs Classification Based Two-side Cross Domain Collaborative Filtering by inferring intrinsic user and item features

Published:2018-02 Issue: Volume:141 Page:80-91
ISSN:0950-7051
Container-title:Knowledge-Based Systems
language:en
Short-container-title:Knowledge-Based Systems

Author:

Yu Xu,Chu Yan,Jiang Feng,Guo Ying,Gong Dunwei

Funder

National Natural Science Foundation of China

Shandong Province Higher Educational Science and Technology Program

Qingdao Indigenous Innovation Program

Natural Science Foundation of Shandong Province

Fundamental Research Funds for Central University

Publisher

Elsevier BV

Subject

Artificial Intelligence,Information Systems and Management,Management Information Systems,Software

Reference46 articles.

1. Recommender systems survey;Bobadilla;Knowl.-Based Syst.,2013

2. Using collaborative filtering to weave an information tapestry;Goldberg;Commun. Acm,1992

3. A semantic enhanced hybrid recommendation approach: A case study of e-Government tourism service recommendation system;Al-Hassan;Decis. Support Syst.,2015

4. Web-page recommendation based on web usage and domain knowledge;Nguyen;IEEE Trans. Knowl. Data Eng.,2014

5. A new user similarity model to improve the accuracy of collaborative filtering;Liu;Knowl.-Based Syst.,2014

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