A collaborative filtering recommendation algorithm based on tag clustering

Rujuan Liu; Zhendong Niu

doi:10.1007/978-3-642-40861-8_27

A collaborative filtering recommendation algorithm based on tag clustering

Rujuan Liu^*, Zhendong Niu

^*Corresponding author for this work

School of Computer Science and Technology

Beijing Institute of Technology

Research output: Chapter in Book/Report/Conference proceeding › Conference contribution › peer-review

6 Citations (Scopus)

Abstract

Social tagging system is applied widely in Web 2.0 nowadays, which is designed to express the user's interest and willingness more accurately. And tag clustering is an important research topic in personalized recommendation of social tagging systems. This paper presents a personalized recommendation method based on tag clustering. In this method, tag clustering is realized by calculating the tag similarity, and recommendation is made based on tag clustering results. Experiments using CiteULike data sets show, proposed method can optimize ranking of objective resources, and help users to discover new resources easier.

Original language	English
Title of host publication	Future Information Technology, FutureTech 2013
Publisher	Springer Verlag
Pages	177-183
Number of pages	7
ISBN (Print)	9783642408601
DOIs	https://doi.org/10.1007/978-3-642-40861-8_27
Publication status	Published - 2014
Event	8th FTRA International Conference on Future Information Technology, FutureTech 2013 - Gwangju, Korea, Republic of Duration: 4 Sept 2013 → 6 Sept 2013

Publication series

Name	Lecture Notes in Electrical Engineering
Volume	276 LNEE
ISSN (Print)	1876-1100
ISSN (Electronic)	1876-1119

Conference

Conference	8th FTRA International Conference on Future Information Technology, FutureTech 2013
Country/Territory	Korea, Republic of
City	Gwangju
Period	4/09/13 → 6/09/13

Keywords

Personalized Recommendation
Social Networks
Tag Clustering

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10.1007/978-3-642-40861-8_27

Cite this

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title = "A collaborative filtering recommendation algorithm based on tag clustering",

abstract = "Social tagging system is applied widely in Web 2.0 nowadays, which is designed to express the user's interest and willingness more accurately. And tag clustering is an important research topic in personalized recommendation of social tagging systems. This paper presents a personalized recommendation method based on tag clustering. In this method, tag clustering is realized by calculating the tag similarity, and recommendation is made based on tag clustering results. Experiments using CiteULike data sets show, proposed method can optimize ranking of objective resources, and help users to discover new resources easier.",

keywords = "Personalized Recommendation, Social Networks, Tag Clustering",

author = "Rujuan Liu and Zhendong Niu",

year = "2014",

doi = "10.1007/978-3-642-40861-8_27",

language = "English",

isbn = "9783642408601",

series = "Lecture Notes in Electrical Engineering",

publisher = "Springer Verlag",

pages = "177--183",

booktitle = "Future Information Technology, FutureTech 2013",

address = "Germany",

note = "8th FTRA International Conference on Future Information Technology, FutureTech 2013 ; Conference date: 04-09-2013 Through 06-09-2013",

}

Liu, R & Niu, Z 2014, A collaborative filtering recommendation algorithm based on tag clustering. in Future Information Technology, FutureTech 2013. Lecture Notes in Electrical Engineering, vol. 276 LNEE, Springer Verlag, pp. 177-183, 8th FTRA International Conference on Future Information Technology, FutureTech 2013, Gwangju, Korea, Republic of, 4/09/13. https://doi.org/10.1007/978-3-642-40861-8_27

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AU - Liu, Rujuan

AU - Niu, Zhendong

PY - 2014

Y1 - 2014

N2 - Social tagging system is applied widely in Web 2.0 nowadays, which is designed to express the user's interest and willingness more accurately. And tag clustering is an important research topic in personalized recommendation of social tagging systems. This paper presents a personalized recommendation method based on tag clustering. In this method, tag clustering is realized by calculating the tag similarity, and recommendation is made based on tag clustering results. Experiments using CiteULike data sets show, proposed method can optimize ranking of objective resources, and help users to discover new resources easier.

AB - Social tagging system is applied widely in Web 2.0 nowadays, which is designed to express the user's interest and willingness more accurately. And tag clustering is an important research topic in personalized recommendation of social tagging systems. This paper presents a personalized recommendation method based on tag clustering. In this method, tag clustering is realized by calculating the tag similarity, and recommendation is made based on tag clustering results. Experiments using CiteULike data sets show, proposed method can optimize ranking of objective resources, and help users to discover new resources easier.

KW - Personalized Recommendation

KW - Social Networks

KW - Tag Clustering

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U2 - 10.1007/978-3-642-40861-8_27

DO - 10.1007/978-3-642-40861-8_27

M3 - Conference contribution

AN - SCOPUS:84899788715

SN - 9783642408601

T3 - Lecture Notes in Electrical Engineering

SP - 177

EP - 183

BT - Future Information Technology, FutureTech 2013

PB - Springer Verlag

T2 - 8th FTRA International Conference on Future Information Technology, FutureTech 2013

Y2 - 4 September 2013 through 6 September 2013

ER -

A collaborative filtering recommendation algorithm based on tag clustering

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