Details
| Originalsprache | Englisch |
|---|---|
| Titel des Sammelwerks | Advances in Information Retrieval |
| Untertitel | 30th European Conference on IR Research, ECIR 2008, Proceedings |
| Herausgeber (Verlag) | Springer Verlag |
| Seiten | 564-569 |
| Seitenumfang | 6 |
| ISBN (elektronisch) | 978-3-540-78646-7 |
| ISBN (Print) | 978-3-540-78645-0 |
| Publikationsstatus | Veröffentlicht - 2008 |
| Veranstaltung | 30th Annual European Conference on Information Retrieval, ECIR 2008 - Glasgow, Großbritannien / Vereinigtes Königreich Dauer: 30 März 2008 → 3 Apr. 2008 |
Publikationsreihe
| Name | Lecture Notes in Computer Science (including subseries Lecture Notes in Artificial Intelligence and Lecture Notes in Bioinformatics) |
|---|---|
| Band | 4956 LNCS |
| ISSN (Print) | 0302-9743 |
| ISSN (elektronisch) | 1611-3349 |
Abstract
In the context of Web Search, clustering based engines are emerging as an alternative for the classical ones. In this paper we analyse different possible ranking algorithms for ordering clusters of documents within a search result. More specifically, we investigate approaches based on document rankings, on the similarities between the user query and the search results, on the quality of the produced clusters, as well as some document independent approaches. Even though we use a topic based hierarchy for categorizing the URLs, our metrics can be applied to other clusters as well. An empirical analysis with a group of 20 subjects showed that the average similarity between the user query and the documents within each category yields the best cluster ranking.
ASJC Scopus Sachgebiete
- Mathematik (insg.)
- Theoretische Informatik
- Informatik (insg.)
- Allgemeine Computerwissenschaft
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Advances in Information Retrieval: 30th European Conference on IR Research, ECIR 2008, Proceedings. Springer Verlag, 2008. S. 564-569 (Lecture Notes in Computer Science (including subseries Lecture Notes in Artificial Intelligence and Lecture Notes in Bioinformatics); Band 4956 LNCS).
Publikation: Beitrag in Buch/Bericht/Sammelwerk/Konferenzband › Aufsatz in Konferenzband › Forschung › Peer-Review
}
TY - GEN
T1 - Ranking categories for web search
AU - Demartini, Gianluca
AU - Chirita, Paul Alexandru
AU - Brunkhorst, Ingo
AU - Nejdl, Wolfgang
PY - 2008
Y1 - 2008
N2 - In the context of Web Search, clustering based engines are emerging as an alternative for the classical ones. In this paper we analyse different possible ranking algorithms for ordering clusters of documents within a search result. More specifically, we investigate approaches based on document rankings, on the similarities between the user query and the search results, on the quality of the produced clusters, as well as some document independent approaches. Even though we use a topic based hierarchy for categorizing the URLs, our metrics can be applied to other clusters as well. An empirical analysis with a group of 20 subjects showed that the average similarity between the user query and the documents within each category yields the best cluster ranking.
AB - In the context of Web Search, clustering based engines are emerging as an alternative for the classical ones. In this paper we analyse different possible ranking algorithms for ordering clusters of documents within a search result. More specifically, we investigate approaches based on document rankings, on the similarities between the user query and the search results, on the quality of the produced clusters, as well as some document independent approaches. Even though we use a topic based hierarchy for categorizing the URLs, our metrics can be applied to other clusters as well. An empirical analysis with a group of 20 subjects showed that the average similarity between the user query and the documents within each category yields the best cluster ranking.
UR - http://www.scopus.com/inward/record.url?scp=41849138626&partnerID=8YFLogxK
U2 - 10.1007/978-3-540-78646-7_56
DO - 10.1007/978-3-540-78646-7_56
M3 - Conference contribution
AN - SCOPUS:41849138626
SN - 978-3-540-78645-0
T3 - Lecture Notes in Computer Science (including subseries Lecture Notes in Artificial Intelligence and Lecture Notes in Bioinformatics)
SP - 564
EP - 569
BT - Advances in Information Retrieval
PB - Springer Verlag
T2 - 30th Annual European Conference on Information Retrieval, ECIR 2008
Y2 - 30 March 2008 through 3 April 2008
ER -