Abstract
Purpose - Web content has been widely used for recommending personal webpages. Despite its popularity, the content-based approach regards a webpage simply as a piece of text, thereby often resulting in less authoritative recommendations of webpages. This paper aims to propose novel approaches that utilise other sources of information pertaining to webpages to facilitate the automatic construction of an authoritative web recommender system. Design/methodology/approach - In this research, four approaches that exploit hyperlink structure, web content and web-usage logs for making recommendations are proposed. The proposed approaches have been implemented as a prototype system, called the authoritative web recommender (AWR) system. An evaluation using the web-usage logs and the corresponding pages of a university web site was performed. Findings - The results from the evaluations using empirical data demonstrate that the four proposed approaches outperform the traditional content-only approach. Originality/value - This paper describes a novel way to combine information retrieval, usage mining and hyperlink structure analysis techniques to find relevant and authoritative webpages for recommendation.
| Original language | English |
|---|---|
| Pages (from-to) | 362-375 |
| Number of pages | 14 |
| Journal | Online Information Review |
| Volume | 33 |
| Issue number | 2 |
| DOIs | |
| Publication status | Published - 2009 Apr 17 |
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All Science Journal Classification (ASJC) codes
- Information Systems
- Computer Science Applications
- Library and Information Sciences
Cite this
}
Increasing the authoritativeness of web recommendations using PageRank-based approaches. / Yang, Wan-Shiou; Jan, Yuan Shuenn.
In: Online Information Review, Vol. 33, No. 2, 17.04.2009, p. 362-375.Research output: Contribution to journal › Article
TY - JOUR
T1 - Increasing the authoritativeness of web recommendations using PageRank-based approaches
AU - Yang, Wan-Shiou
AU - Jan, Yuan Shuenn
PY - 2009/4/17
Y1 - 2009/4/17
N2 - Purpose - Web content has been widely used for recommending personal webpages. Despite its popularity, the content-based approach regards a webpage simply as a piece of text, thereby often resulting in less authoritative recommendations of webpages. This paper aims to propose novel approaches that utilise other sources of information pertaining to webpages to facilitate the automatic construction of an authoritative web recommender system. Design/methodology/approach - In this research, four approaches that exploit hyperlink structure, web content and web-usage logs for making recommendations are proposed. The proposed approaches have been implemented as a prototype system, called the authoritative web recommender (AWR) system. An evaluation using the web-usage logs and the corresponding pages of a university web site was performed. Findings - The results from the evaluations using empirical data demonstrate that the four proposed approaches outperform the traditional content-only approach. Originality/value - This paper describes a novel way to combine information retrieval, usage mining and hyperlink structure analysis techniques to find relevant and authoritative webpages for recommendation.
AB - Purpose - Web content has been widely used for recommending personal webpages. Despite its popularity, the content-based approach regards a webpage simply as a piece of text, thereby often resulting in less authoritative recommendations of webpages. This paper aims to propose novel approaches that utilise other sources of information pertaining to webpages to facilitate the automatic construction of an authoritative web recommender system. Design/methodology/approach - In this research, four approaches that exploit hyperlink structure, web content and web-usage logs for making recommendations are proposed. The proposed approaches have been implemented as a prototype system, called the authoritative web recommender (AWR) system. An evaluation using the web-usage logs and the corresponding pages of a university web site was performed. Findings - The results from the evaluations using empirical data demonstrate that the four proposed approaches outperform the traditional content-only approach. Originality/value - This paper describes a novel way to combine information retrieval, usage mining and hyperlink structure analysis techniques to find relevant and authoritative webpages for recommendation.
UR - http://www.scopus.com/inward/record.url?scp=70249126938&partnerID=8YFLogxK
UR - http://www.scopus.com/inward/citedby.url?scp=70249126938&partnerID=8YFLogxK
U2 - 10.1108/14684520910951267
DO - 10.1108/14684520910951267
M3 - Article
AN - SCOPUS:70249126938
VL - 33
SP - 362
EP - 375
JO - Online Information Review
JF - Online Information Review
SN - 1468-4527
IS - 2
ER -