Details
| Original language | English |
|---|---|
| Title of host publication | SIGIR 2005 |
| Subtitle of host publication | Proceedings of the 28th Annual International ACM SIGIR Conference on Research and Development in Information Retrieval |
| Publisher | Association for Computing Machinery (ACM) |
| Pages | 178-185 |
| Number of pages | 8 |
| ISBN (print) | 1595930345, 9781595930347 |
| Publication status | Published - 15 Aug 2005 |
| Event | 28th Annual International ACM SIGIR Conference on Research and Development in Information Retrieval, SIGIR 2005 - Salvador, Brazil Duration: 15 Aug 2005 → 19 Aug 2005 |
Publication series
| Name | SIGIR 2005 - Proceedings of the 28th Annual International ACM SIGIR Conference on Research and Development in Information Retrieval |
|---|
Abstract
The Open Directory Project is clearly one of the largest collaborative efforts to manually annotate web pages. This effort involves over 65,000 editors and resulted in metadata specifying topic and importance for more than 4 million web pages. Still, given that this number is just about 0.05 percent of the Web pages indexed by Google, is this effort enough to make a difference? In this paper we discuss how these metadata can be exploited to achieve high quality personalized web search. First, we address this by introducing an additional criterion for web page ranking, namely the distance between a user profile defined using ODP topics and the sets of ODP topics covered by each URL returned in regular web search. We empirically show that this enhancement yields better results than current web search using Google. Then, in the second part of the paper, we investigate the boundaries of biasing PageRank on subtopics of the ODP in order to automatically extend these metadata to the whole web.
Keywords
- biased pageRank, metadata, open directory, personalized search
ASJC Scopus subject areas
- Computer Science(all)
- Information Systems
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SIGIR 2005: Proceedings of the 28th Annual International ACM SIGIR Conference on Research and Development in Information Retrieval. Association for Computing Machinery (ACM), 2005. p. 178-185 (SIGIR 2005 - Proceedings of the 28th Annual International ACM SIGIR Conference on Research and Development in Information Retrieval).
Research output: Chapter in book/report/conference proceeding › Conference contribution › Research › peer review
}
TY - GEN
T1 - Using ODP metadata to personalize search
AU - Chirita, Paul Alexandru
AU - Nejdl, Wolfgang
AU - Paiu, Raluca
AU - Kohlschütter, Christian
PY - 2005/8/15
Y1 - 2005/8/15
N2 - The Open Directory Project is clearly one of the largest collaborative efforts to manually annotate web pages. This effort involves over 65,000 editors and resulted in metadata specifying topic and importance for more than 4 million web pages. Still, given that this number is just about 0.05 percent of the Web pages indexed by Google, is this effort enough to make a difference? In this paper we discuss how these metadata can be exploited to achieve high quality personalized web search. First, we address this by introducing an additional criterion for web page ranking, namely the distance between a user profile defined using ODP topics and the sets of ODP topics covered by each URL returned in regular web search. We empirically show that this enhancement yields better results than current web search using Google. Then, in the second part of the paper, we investigate the boundaries of biasing PageRank on subtopics of the ODP in order to automatically extend these metadata to the whole web.
AB - The Open Directory Project is clearly one of the largest collaborative efforts to manually annotate web pages. This effort involves over 65,000 editors and resulted in metadata specifying topic and importance for more than 4 million web pages. Still, given that this number is just about 0.05 percent of the Web pages indexed by Google, is this effort enough to make a difference? In this paper we discuss how these metadata can be exploited to achieve high quality personalized web search. First, we address this by introducing an additional criterion for web page ranking, namely the distance between a user profile defined using ODP topics and the sets of ODP topics covered by each URL returned in regular web search. We empirically show that this enhancement yields better results than current web search using Google. Then, in the second part of the paper, we investigate the boundaries of biasing PageRank on subtopics of the ODP in order to automatically extend these metadata to the whole web.
KW - biased pageRank
KW - metadata
KW - open directory
KW - personalized search
UR - http://www.scopus.com/inward/record.url?scp=84885614997&partnerID=8YFLogxK
U2 - 10.1145/1076034.1076067
DO - 10.1145/1076034.1076067
M3 - Conference contribution
AN - SCOPUS:84885614997
SN - 1595930345
SN - 9781595930347
T3 - SIGIR 2005 - Proceedings of the 28th Annual International ACM SIGIR Conference on Research and Development in Information Retrieval
SP - 178
EP - 185
BT - SIGIR 2005
PB - Association for Computing Machinery (ACM)
T2 - 28th Annual International ACM SIGIR Conference on Research and Development in Information Retrieval, SIGIR 2005
Y2 - 15 August 2005 through 19 August 2005
ER -