An Approach For Applying Social Networks Information To Information Recommendation

Yeunjung Kim; Minsoo Lee

doi:10.1007/978-3-662-45402-2_182

An Approach For Applying Social Networks Information To Information Recommendation

Yeunjung Kim, Minsoo Lee

Department of Computer Science & Engineering

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

Abstract

Due to the rapid development of the Internet and need for recommendation systems, there have been several recommendation systems using the various information on the Internet and more and more systems are using the SNS information. However, most of them only consider the simple direct friend relationships. In this paper we use the intimacy and similarity between users on the SNS to compute the weight of an evaluating person for recommendation purpose. The intimacy between users considers the direct and distant friend relationships on an SNS which contains direction and importance information among friends. The similarity between users is computed by using the mutual friends as well as the relationship between the user’s preference and the given item. In order to enhance the objectivity among user’s evaluations, the evaluation was performed on several item attributes. We have used real SNS data to carry out experiments and show how well the intimacy and similarity can predict the target user’s evaluation ratings.

Original language	English
Title of host publication	Computer Science and Its Applications - Ubiquitous Information Technologies
Editors	Hwa Young Jeong, Ivan Stojmenovic, James J. Park, Gangman Yi
Publisher	Springer Verlag
Pages	1307-1314
Number of pages	8
ISBN (Electronic)	9783662454015
DOIs	https://doi.org/10.1007/978-3-662-45402-2_182
State	Published - 2015
Event	6th FTRA International Conference on Computer Science and its Applications, CSA 2014 - Guam, United States Duration: 17 Dec 2014 → 19 Dec 2014

Publication series

Name	Lecture Notes in Electrical Engineering
Volume	330
ISSN (Print)	1876-1100
ISSN (Electronic)	1876-1119

Conference

Conference	6th FTRA International Conference on Computer Science and its Applications, CSA 2014
Country/Territory	United States
City	Guam
Period	17/12/14 → 19/12/14

Bibliographical note

Publisher Copyright:
© Springer-Verlag Berlin Heidelberg 2015.

Keywords

Intimacy measurement
Similarity measurement
Social information filtering
Social recommender algorithm
Social recommender system

Access to Document

10.1007/978-3-662-45402-2_182

Cite this

Kim, Y., & Lee, M. (2015). An Approach For Applying Social Networks Information To Information Recommendation. In H. Y. Jeong, I. Stojmenovic, J. J. Park, & G. Yi (Eds.), Computer Science and Its Applications - Ubiquitous Information Technologies (pp. 1307-1314). (Lecture Notes in Electrical Engineering; Vol. 330). Springer Verlag. https://doi.org/10.1007/978-3-662-45402-2_182

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title = "An Approach For Applying Social Networks Information To Information Recommendation",

abstract = "Due to the rapid development of the Internet and need for recommendation systems, there have been several recommendation systems using the various information on the Internet and more and more systems are using the SNS information. However, most of them only consider the simple direct friend relationships. In this paper we use the intimacy and similarity between users on the SNS to compute the weight of an evaluating person for recommendation purpose. The intimacy between users considers the direct and distant friend relationships on an SNS which contains direction and importance information among friends. The similarity between users is computed by using the mutual friends as well as the relationship between the user{\textquoteright}s preference and the given item. In order to enhance the objectivity among user{\textquoteright}s evaluations, the evaluation was performed on several item attributes. We have used real SNS data to carry out experiments and show how well the intimacy and similarity can predict the target user{\textquoteright}s evaluation ratings.",

keywords = "Intimacy measurement, Similarity measurement, Social information filtering, Social recommender algorithm, Social recommender system",

author = "Yeunjung Kim and Minsoo Lee",

note = "Publisher Copyright: {\textcopyright} Springer-Verlag Berlin Heidelberg 2015.; 6th FTRA International Conference on Computer Science and its Applications, CSA 2014 ; Conference date: 17-12-2014 Through 19-12-2014",

year = "2015",

doi = "10.1007/978-3-662-45402-2_182",

language = "English",

series = "Lecture Notes in Electrical Engineering",

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Kim, Y & Lee, M 2015, An Approach For Applying Social Networks Information To Information Recommendation. in HY Jeong, I Stojmenovic, JJ Park & G Yi (eds), Computer Science and Its Applications - Ubiquitous Information Technologies. Lecture Notes in Electrical Engineering, vol. 330, Springer Verlag, pp. 1307-1314, 6th FTRA International Conference on Computer Science and its Applications, CSA 2014, Guam, United States, 17/12/14. https://doi.org/10.1007/978-3-662-45402-2_182

An Approach For Applying Social Networks Information To Information Recommendation. / Kim, Yeunjung; Lee, Minsoo.
Computer Science and Its Applications - Ubiquitous Information Technologies. ed. / Hwa Young Jeong; Ivan Stojmenovic; James J. Park; Gangman Yi. Springer Verlag, 2015. p. 1307-1314 (Lecture Notes in Electrical Engineering; Vol. 330).

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

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N2 - Due to the rapid development of the Internet and need for recommendation systems, there have been several recommendation systems using the various information on the Internet and more and more systems are using the SNS information. However, most of them only consider the simple direct friend relationships. In this paper we use the intimacy and similarity between users on the SNS to compute the weight of an evaluating person for recommendation purpose. The intimacy between users considers the direct and distant friend relationships on an SNS which contains direction and importance information among friends. The similarity between users is computed by using the mutual friends as well as the relationship between the user’s preference and the given item. In order to enhance the objectivity among user’s evaluations, the evaluation was performed on several item attributes. We have used real SNS data to carry out experiments and show how well the intimacy and similarity can predict the target user’s evaluation ratings.

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An Approach For Applying Social Networks Information To Information Recommendation

Abstract

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Bibliographical note

Keywords

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