A Method based on One-class SVM for News Recommendation

In order to provide intelligent recommendation and personalized service for users on news website, this paper presents a method based on One-Class SVM for news recommendation algorithm. By analyzing the news webpages and user's browsing history, and by building One-Class SVM model, this algorit...

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Published inProcedia computer science Vol. 31; pp. 281 - 290
Main Authors Cui, Limeng, Shi, Yong
Format Journal Article
LanguageEnglish
Published Elsevier B.V 2014
Subjects
Hierarchical recommendation algorithm
News recommendation
One-Class SVM
Similarity calculation
Vector Space Model (VSM)
Hierarchical recommendation algorithm
News recommendation
One-Class SVM
Similarity calculation
Vector Space Model (VSM)
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Abstract In order to provide intelligent recommendation and personalized service for users on news website, this paper presents a method based on One-Class SVM for news recommendation algorithm. By analyzing the news webpages and user's browsing history, and by building One-Class SVM model, this algorithm can recommend news for user. The main work of this paper is to study this news recommendation algorithm and to show its experimental results under Dot NET platform. First, this algorithm preprocesses the webpages from Sogou Labs, each of which has its inherent domain and builds One-Class SVM models for these domains. Next, it builds user interest models for each user by analyzing their browsing histories. Then it finds the user's most interested domains by comparing each domain models and user interest model. Finally, it utilizes the webpages of these domains and user's browsing history to build One-Class SVM model to calculate the most relevant webpages to user interest, and recommends these webpages to user. This algorithm takes the lead in calculate the similarity between user interests and webpages using One-Class SVM model and apply hierarchical model to make the results more accurate. From the results, we can find that this algorithm is running pretty well.
AbstractList In order to provide intelligent recommendation and personalized service for users on news website, this paper presents a method based on One-Class SVM for news recommendation algorithm. By analyzing the news webpages and user's browsing history, and by building One-Class SVM model, this algorithm can recommend news for user. The main work of this paper is to study this news recommendation algorithm and to show its experimental results under Dot NET platform. First, this algorithm preprocesses the webpages from Sogou Labs, each of which has its inherent domain and builds One-Class SVM models for these domains. Next, it builds user interest models for each user by analyzing their browsing histories. Then it finds the user's most interested domains by comparing each domain models and user interest model. Finally, it utilizes the webpages of these domains and user's browsing history to build One-Class SVM model to calculate the most relevant webpages to user interest, and recommends these webpages to user. This algorithm takes the lead in calculate the similarity between user interests and webpages using One-Class SVM model and apply hierarchical model to make the results more accurate. From the results, we can find that this algorithm is running pretty well.
Author Shi, Yong
Cui, Limeng
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Keywords Hierarchical recommendation algorithm
News recommendation
One-Class SVM
Similarity calculation
Vector Space Model (VSM)
Language English
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References 2006, 33(11): 86-88.
2007, 33(17): 196-198.
Manevitz L M, Yousef M. One-class SVMs for document classification.
Springer Berlin Heidelberg, 2005: 123-135.
IEEE Transactions on, 2005, 17(6): 734-749.
2009, 6: 002.
Kamba T, Sakagami H, Koseki Y. ANATAGONOMY: a personalized newspaper on the World Wide Web.
Lin S, Liu Z. Parameter selection in SVM with RBF kernel function.
Yong Shi, Yingjie Tian, Gang Kou, Yi Peng, Jianping Li.
Lin S M, Wang G S, Chen Y Q. User modeling and feature selection in personalized recommending system.
Schölkopf B, Platt J C, Shawe-Taylor J, et al. Estimating the support of a high-dimensional distribution. Neural computation, 2001, 13(7): 1443-1471.
SHAO Hua, GAO Feng-Rong, XING Chun-Xiao, JIANG Li-Hua. A Hierarchical Webpage Recommendation Algorithm Based on Vector Space Model.
2002, 2: 139-154.
2007, 35(2): 163.
(Natural Science Edition), 2012, 1: 009.
Adomavicius G, Tuzhilin A. Toward the next generation of recommender systems: A survey of the state-of-the-art and possible extensions.
1999, 8.
Wang X M, Peng H. One-class SVM Based on Data Distribution.
Yajima Y. One-class support vector machines for recommendation tasks.
de Campos L M, Fernández-Luna J M, Gómez M, et al. A decision-based approach for recommending in hierarchical domains.
FENG A, LIU X, SUN T. Embedding Target Data's Structural Distribution Information into-One-Class SVM and Its Linear Programming Algorithm.
Hu W C, Chen Y, Schmalz M S, et al. An overview of world wide web search technologies. The proceedings of 5th World Multi Conference on Systems, Cybernetics, Informatics, SCI2001, Orlando, Florida. 2001: 22-25.
1997, 46(6): 789-803.
Cooley R, Tan P N, Srivastava J. Websift: the web site information filter system.
ACM, 2010: 31-40.
Springer Berlin Heidelberg, 2006: 230-239.
Liu J, Dolan P, Pedersen E R. Personalized news recommendation based on click behavior.
Springer, 2011.
10.1016/j.procs.2014.05.270_bib0010
10.1016/j.procs.2014.05.270_bib0065
10.1016/j.procs.2014.05.270_bib0020
10.1016/j.procs.2014.05.270_bib0075
10.1016/j.procs.2014.05.270_bib0045
10.1016/j.procs.2014.05.270_bib0055
10.1016/j.procs.2014.05.270_bib0025
10.1016/j.procs.2014.05.270_bib0035
10.1016/j.procs.2014.05.270_bib0005
10.1016/j.procs.2014.05.270_bib0015
10.1016/j.procs.2014.05.270_bib0070
10.1016/j.procs.2014.05.270_bib0050
10.1016/j.procs.2014.05.270_bib0060
10.1016/j.procs.2014.05.270_bib0030
10.1016/j.procs.2014.05.270_bib0040
References_xml – reference: Cooley R, Tan P N, Srivastava J. Websift: the web site information filter system.
– reference: , 1997, 46(6): 789-803.
– reference: Manevitz L M, Yousef M. One-class SVMs for document classification.
– reference: , 2006, 33(11): 86-88.
– reference: Wang X M, Peng H. One-class SVM Based on Data Distribution.
– reference: Schölkopf B, Platt J C, Shawe-Taylor J, et al. Estimating the support of a high-dimensional distribution. Neural computation, 2001, 13(7): 1443-1471.
– reference: , IEEE Transactions on, 2005, 17(6): 734-749.
– reference: Hu W C, Chen Y, Schmalz M S, et al. An overview of world wide web search technologies. The proceedings of 5th World Multi Conference on Systems, Cybernetics, Informatics, SCI2001, Orlando, Florida. 2001: 22-25.
– reference: , 2007, 33(17): 196-198.
– reference: de Campos L M, Fernández-Luna J M, Gómez M, et al. A decision-based approach for recommending in hierarchical domains.
– reference: Springer, 2011.
– reference: ACM, 2010: 31-40.
– reference: , 2009, 6: 002.
– reference: Adomavicius G, Tuzhilin A. Toward the next generation of recommender systems: A survey of the state-of-the-art and possible extensions.
– reference: FENG A, LIU X, SUN T. Embedding Target Data's Structural Distribution Information into-One-Class SVM and Its Linear Programming Algorithm.
– reference: 1999, 8.
– reference: , 2007, 35(2): 163.
– reference: Lin S, Liu Z. Parameter selection in SVM with RBF kernel function.
– reference: , 2002, 2: 139-154.
– reference: SHAO Hua, GAO Feng-Rong, XING Chun-Xiao, JIANG Li-Hua. A Hierarchical Webpage Recommendation Algorithm Based on Vector Space Model.
– reference: (Natural Science Edition), 2012, 1: 009.
– reference: Lin S M, Wang G S, Chen Y Q. User modeling and feature selection in personalized recommending system.
– reference: Springer Berlin Heidelberg, 2006: 230-239.
– reference: Yajima Y. One-class support vector machines for recommendation tasks.
– reference: . Springer Berlin Heidelberg, 2005: 123-135.
– reference: Kamba T, Sakagami H, Koseki Y. ANATAGONOMY: a personalized newspaper on the World Wide Web.
– reference: Liu J, Dolan P, Pedersen E R. Personalized news recommendation based on click behavior.
– reference: Yong Shi, Yingjie Tian, Gang Kou, Yi Peng, Jianping Li.
– ident: 10.1016/j.procs.2014.05.270_bib0015
– ident: 10.1016/j.procs.2014.05.270_bib0065
– ident: 10.1016/j.procs.2014.05.270_bib0055
  doi: 10.1007/978-0-85729-504-0
– ident: 10.1016/j.procs.2014.05.270_bib0070
– ident: 10.1016/j.procs.2014.05.270_bib0010
  doi: 10.1145/1719970.1719976
– ident: 10.1016/j.procs.2014.05.270_bib0050
  doi: 10.1162/089976601750264965
– ident: 10.1016/j.procs.2014.05.270_bib0060
  doi: 10.1109/TKDE.2005.99
– ident: 10.1016/j.procs.2014.05.270_bib0035
– ident: 10.1016/j.procs.2014.05.270_bib0030
– ident: 10.1016/j.procs.2014.05.270_bib0075
– ident: 10.1016/j.procs.2014.05.270_bib0045
– ident: 10.1016/j.procs.2014.05.270_bib0040
  doi: 10.1007/11518655_12
– ident: 10.1016/j.procs.2014.05.270_bib0020
  doi: 10.1006/ijhc.1996.0113
– ident: 10.1016/j.procs.2014.05.270_bib0005
– ident: 10.1016/j.procs.2014.05.270_bib0025
  doi: 10.1007/11731139_28
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Snippet In order to provide intelligent recommendation and personalized service for users on news website, this paper presents a method based on One-Class SVM for news...
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SubjectTerms Hierarchical recommendation algorithm
News recommendation
One-Class SVM
Similarity calculation
Vector Space Model (VSM)
Title A Method based on One-class SVM for News Recommendation
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