Ranking categories for web search

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Original languageEnglish
Title of host publicationAdvances in Information Retrieval
Subtitle of host publication30th European Conference on IR Research, ECIR 2008, Proceedings
PublisherSpringer Verlag
Pages564-569
Number of pages6
ISBN (electronic)978-3-540-78646-7
ISBN (print)978-3-540-78645-0
Publication statusPublished - 2008
Event30th Annual European Conference on Information Retrieval, ECIR 2008 - Glasgow, United Kingdom (UK)
Duration: 30 Mar 20083 Apr 2008

Publication series

NameLecture Notes in Computer Science (including subseries Lecture Notes in Artificial Intelligence and Lecture Notes in Bioinformatics)
Volume4956 LNCS
ISSN (Print)0302-9743
ISSN (electronic)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.

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Cite this

Ranking categories for web search. / Demartini, Gianluca; Chirita, Paul Alexandru; Brunkhorst, Ingo et al.
Advances in Information Retrieval: 30th European Conference on IR Research, ECIR 2008, Proceedings. Springer Verlag, 2008. p. 564-569 (Lecture Notes in Computer Science (including subseries Lecture Notes in Artificial Intelligence and Lecture Notes in Bioinformatics); Vol. 4956 LNCS).

Research output: Chapter in book/report/conference proceedingConference contributionResearchpeer review

Demartini, G, Chirita, PA, Brunkhorst, I & Nejdl, W 2008, Ranking categories for web search. in Advances in Information Retrieval: 30th European Conference on IR Research, ECIR 2008, Proceedings. Lecture Notes in Computer Science (including subseries Lecture Notes in Artificial Intelligence and Lecture Notes in Bioinformatics), vol. 4956 LNCS, Springer Verlag, pp. 564-569, 30th Annual European Conference on Information Retrieval, ECIR 2008, Glasgow, United Kingdom (UK), 30 Mar 2008. https://doi.org/10.1007/978-3-540-78646-7_56
Demartini, G., Chirita, P. A., Brunkhorst, I., & Nejdl, W. (2008). Ranking categories for web search. In Advances in Information Retrieval: 30th European Conference on IR Research, ECIR 2008, Proceedings (pp. 564-569). (Lecture Notes in Computer Science (including subseries Lecture Notes in Artificial Intelligence and Lecture Notes in Bioinformatics); Vol. 4956 LNCS). Springer Verlag. https://doi.org/10.1007/978-3-540-78646-7_56
Demartini G, Chirita PA, Brunkhorst I, Nejdl W. Ranking categories for web search. In Advances in Information Retrieval: 30th European Conference on IR Research, ECIR 2008, Proceedings. Springer Verlag. 2008. p. 564-569. (Lecture Notes in Computer Science (including subseries Lecture Notes in Artificial Intelligence and Lecture Notes in Bioinformatics)). doi: 10.1007/978-3-540-78646-7_56
Demartini, Gianluca ; Chirita, Paul Alexandru ; Brunkhorst, Ingo et al. / Ranking categories for web search. Advances in Information Retrieval: 30th European Conference on IR Research, ECIR 2008, Proceedings. Springer Verlag, 2008. pp. 564-569 (Lecture Notes in Computer Science (including subseries Lecture Notes in Artificial Intelligence and Lecture Notes in Bioinformatics)).
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