Improvement of pseudo-voting method in recommender systems

Takayuki Uda; Tetsuo Kinoshita

Improvement of pseudo-voting method in recommender systems

Takayuki Uda, Tetsuo Kinoshita

Systems & Software Division

Research output: Contribution to conference › Paper › peer-review

Abstract

Collaborative filtering (CF) is widely used as an engine for recommender systems that identify items preferred by users. The importance of such recommender systems has been recognized in the fields of e-commerce, advertisement systems, and so on. However, the challenge of achieving a trade-off between the "coverage of recommendation" and "accuracy of the predicted score" still exists. Hence, a new recommendation system that utilizes the features of items and the pseudo-voting method is proposed to improve both the coverage and the accuracy. Furthermore, the effect of the proposed system is evaluated in this study.

Original language	English
Publication status	Published - 2007 Jan 1
Event	1st Workshop on Information Credibility on the Web, WICOW 2007 - Miyazaki, Japan Duration: 2007 Jun 19 → 2007 Jun 19

Other

Other	1st Workshop on Information Credibility on the Web, WICOW 2007
Country/Territory	Japan
City	Miyazaki
Period	07/6/19 → 07/6/19

Keywords

Collaborative filtering
Feature analysis
Pseudo-voting method

ASJC Scopus subject areas

Artificial Intelligence
Computer Science Applications

Cite this

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title = "Improvement of pseudo-voting method in recommender systems",

abstract = "Collaborative filtering (CF) is widely used as an engine for recommender systems that identify items preferred by users. The importance of such recommender systems has been recognized in the fields of e-commerce, advertisement systems, and so on. However, the challenge of achieving a trade-off between the {"}coverage of recommendation{"} and {"}accuracy of the predicted score{"} still exists. Hence, a new recommendation system that utilizes the features of items and the pseudo-voting method is proposed to improve both the coverage and the accuracy. Furthermore, the effect of the proposed system is evaluated in this study.",

keywords = "Collaborative filtering, Feature analysis, Pseudo-voting method",

author = "Takayuki Uda and Tetsuo Kinoshita",

year = "2007",

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language = "English",

note = "1st Workshop on Information Credibility on the Web, WICOW 2007 ; Conference date: 19-06-2007 Through 19-06-2007",

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TY - CONF

T1 - Improvement of pseudo-voting method in recommender systems

AU - Uda, Takayuki

AU - Kinoshita, Tetsuo

PY - 2007/1/1

Y1 - 2007/1/1

N2 - Collaborative filtering (CF) is widely used as an engine for recommender systems that identify items preferred by users. The importance of such recommender systems has been recognized in the fields of e-commerce, advertisement systems, and so on. However, the challenge of achieving a trade-off between the "coverage of recommendation" and "accuracy of the predicted score" still exists. Hence, a new recommendation system that utilizes the features of items and the pseudo-voting method is proposed to improve both the coverage and the accuracy. Furthermore, the effect of the proposed system is evaluated in this study.

AB - Collaborative filtering (CF) is widely used as an engine for recommender systems that identify items preferred by users. The importance of such recommender systems has been recognized in the fields of e-commerce, advertisement systems, and so on. However, the challenge of achieving a trade-off between the "coverage of recommendation" and "accuracy of the predicted score" still exists. Hence, a new recommendation system that utilizes the features of items and the pseudo-voting method is proposed to improve both the coverage and the accuracy. Furthermore, the effect of the proposed system is evaluated in this study.

KW - Collaborative filtering

KW - Feature analysis

KW - Pseudo-voting method

UR - http://www.scopus.com/inward/record.url?scp=84895899352&partnerID=8YFLogxK

UR - http://www.scopus.com/inward/citedby.url?scp=84895899352&partnerID=8YFLogxK

M3 - Paper

AN - SCOPUS:84895899352

T2 - 1st Workshop on Information Credibility on the Web, WICOW 2007

Y2 - 19 June 2007 through 19 June 2007

ER -

Improvement of pseudo-voting method in recommender systems

Abstract

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Keywords

ASJC Scopus subject areas

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