Details
| Originalsprache | Englisch |
|---|---|
| Titel des Sammelwerks | Proceedings |
| Untertitel | IEEE/WIC/ACM International Conference on Web Intelligence, WI 2004 |
| Herausgeber/-innen | N. Zhong, H. Tirri, Y. Yao, L. Zhou |
| Seiten | 632-635 |
| Seitenumfang | 4 |
| Publikationsstatus | Veröffentlicht - 2004 |
| Veranstaltung | IEEE/WIC/ACM International Conference on Web Intelligence, WI 2004 - Beijing, China Dauer: 20 Sept. 2004 → 24 Sept. 2004 |
Publikationsreihe
| Name | Proceedings - IEEE/WIC/ACM International Conference on Web Intelligence, WI 2004 |
|---|
Abstract
Most of the current algorithms for finding related pages are exclusively based on text corpora of the WWW or incorporate only authority or hub values of pages. In this paper, we present HubFinder, a new fast algorithm for finding related pages exploring the link structure of the Web graph. Its criterion for filtering output pages is "pluggable", depending on the user's interests, and may vary from global page ranks to text content, etc. We also introduce HubRank, a new ranking algorithm which gives a more complete view of page "importance" by biasing the authority measure of PageRank towards hub values of pages. Finally, we present an evaluation of these algorithms in order to prove their qualities experimentally.
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Proceedings: IEEE/WIC/ACM International Conference on Web Intelligence, WI 2004. Hrsg. / N. Zhong; H. Tirri; Y. Yao; L. Zhou. 2004. S. 632-635 (Proceedings - IEEE/WIC/ACM International Conference on Web Intelligence, WI 2004).
Publikation: Beitrag in Buch/Bericht/Sammelwerk/Konferenzband › Aufsatz in Konferenzband › Forschung › Peer-Review
}
TY - GEN
T1 - Finding related pages using the link structure of the WWW
AU - Chirita, Paul Alexandra
AU - Olmedilla, Daniel
AU - Nejdl, Wolfgang
PY - 2004
Y1 - 2004
N2 - Most of the current algorithms for finding related pages are exclusively based on text corpora of the WWW or incorporate only authority or hub values of pages. In this paper, we present HubFinder, a new fast algorithm for finding related pages exploring the link structure of the Web graph. Its criterion for filtering output pages is "pluggable", depending on the user's interests, and may vary from global page ranks to text content, etc. We also introduce HubRank, a new ranking algorithm which gives a more complete view of page "importance" by biasing the authority measure of PageRank towards hub values of pages. Finally, we present an evaluation of these algorithms in order to prove their qualities experimentally.
AB - Most of the current algorithms for finding related pages are exclusively based on text corpora of the WWW or incorporate only authority or hub values of pages. In this paper, we present HubFinder, a new fast algorithm for finding related pages exploring the link structure of the Web graph. Its criterion for filtering output pages is "pluggable", depending on the user's interests, and may vary from global page ranks to text content, etc. We also introduce HubRank, a new ranking algorithm which gives a more complete view of page "importance" by biasing the authority measure of PageRank towards hub values of pages. Finally, we present an evaluation of these algorithms in order to prove their qualities experimentally.
UR - http://www.scopus.com/inward/record.url?scp=15544382561&partnerID=8YFLogxK
U2 - 10.1109/WI.2004.10056
DO - 10.1109/WI.2004.10056
M3 - Conference contribution
AN - SCOPUS:15544382561
SN - 0769521002
SN - 9780769521008
T3 - Proceedings - IEEE/WIC/ACM International Conference on Web Intelligence, WI 2004
SP - 632
EP - 635
BT - Proceedings
A2 - Zhong, N.
A2 - Tirri, H.
A2 - Yao, Y.
A2 - Zhou, L.
T2 - IEEE/WIC/ACM International Conference on Web Intelligence, WI 2004
Y2 - 20 September 2004 through 24 September 2004
ER -