Classification of Recommender Expertise in the Wikipedia Recommender System

Publication: Research - peer-reviewJournal article – Annual report year: 2012

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Classification of Recommender Expertise in the Wikipedia Recommender System. / Jensen, Christian D.; Pilkauskas, Povilas; Lefévre, Thomas.

In: Journal of Information Processing, Vol. 19, 2011, p. 345-363.

Publication: Research - peer-reviewJournal article – Annual report year: 2012

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Jensen, Christian D.; Pilkauskas, Povilas; Lefévre, Thomas / Classification of Recommender Expertise in the Wikipedia Recommender System.

In: Journal of Information Processing, Vol. 19, 2011, p. 345-363.

Publication: Research - peer-reviewJournal article – Annual report year: 2012

Bibtex

@article{06c753eb2f654c69ba34f8c01208e3a1,
title = "Classification of Recommender Expertise in the Wikipedia Recommender System",
publisher = "Information Processing Society of Japan",
author = "Jensen, {Christian D.} and Povilas Pilkauskas and Thomas Lefévre",
year = "2011",
doi = "10.2197/ipsjjip.19.345",
volume = "19",
pages = "345--363",
journal = "Journal of Information Processing",

}

RIS

TY - JOUR

T1 - Classification of Recommender Expertise in the Wikipedia Recommender System

A1 - Jensen,Christian D.

A1 - Pilkauskas,Povilas

A1 - Lefévre,Thomas

AU - Jensen,Christian D.

AU - Pilkauskas,Povilas

AU - Lefévre,Thomas

PB - Information Processing Society of Japan

PY - 2011

Y1 - 2011

N2 - The Wikipedia is a web-based encyclopedia, written and edited collaboratively by Internet users. The Wikipedia has an extremely open editorial policy that allows anybody, to create or modify articles. This has promoted a broad and detailed coverage of subjects, but also introduced problems relating to the quality of articles. The Wikipedia Recommender System (WRS) was developed to help users determine the credibility of articles based on feedback from other Wikipedia users. The WRS implements a collaborative filtering system with trust metrics, i.e., it provides a rating of articles which emphasizes feedback from recommenders that the user has agreed with in the past. This exposes the problem that most recommenders are not equally competent in all subject areas. The first WRS prototype did not include an evaluation of the areas of expertise of recommenders, so the trust metric used in the article ratings reflected the average competence of recommenders across all subject areas. We have now developed a new version of the WRS, which evaluates the expertise of recommenders within different subject areas. In order to do this, we need to identify a way to classify the subject area of all the articles in the Wikipedia. In this paper, we examine different ways to classify the subject area of Wikipedia article according to well established knowledge classification schemes. We identify a number of requirements that a classification scheme must meet in order to be useful in the context of the WRS and present an evaluation of four existing knowledge classification schemes with respect to these requirements. This evaluation helped us identify a classification scheme, which we have implemented in the current version of the Wikipedia Recommender System.

AB - The Wikipedia is a web-based encyclopedia, written and edited collaboratively by Internet users. The Wikipedia has an extremely open editorial policy that allows anybody, to create or modify articles. This has promoted a broad and detailed coverage of subjects, but also introduced problems relating to the quality of articles. The Wikipedia Recommender System (WRS) was developed to help users determine the credibility of articles based on feedback from other Wikipedia users. The WRS implements a collaborative filtering system with trust metrics, i.e., it provides a rating of articles which emphasizes feedback from recommenders that the user has agreed with in the past. This exposes the problem that most recommenders are not equally competent in all subject areas. The first WRS prototype did not include an evaluation of the areas of expertise of recommenders, so the trust metric used in the article ratings reflected the average competence of recommenders across all subject areas. We have now developed a new version of the WRS, which evaluates the expertise of recommenders within different subject areas. In order to do this, we need to identify a way to classify the subject area of all the articles in the Wikipedia. In this paper, we examine different ways to classify the subject area of Wikipedia article according to well established knowledge classification schemes. We identify a number of requirements that a classification scheme must meet in order to be useful in the context of the WRS and present an evaluation of four existing knowledge classification schemes with respect to these requirements. This evaluation helped us identify a classification scheme, which we have implemented in the current version of the Wikipedia Recommender System.

UR - https://www.jstage.jst.go.jp/article/ipsjjip/19/0/19_0_345/_article

U2 - 10.2197/ipsjjip.19.345

DO - 10.2197/ipsjjip.19.345

JO - Journal of Information Processing

JF - Journal of Information Processing

VL - 19

SP - 345

EP - 363

ER -