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Browsing-oriented Semantic Faceted Search

Andreas Wagner, Günter Ladwig, Duc Thanh Tran

Veröffentlichung: 2010 Januar
Art der Veröffentlichung: Technical Report
BibTeX

Kurzfassung
Faceted search enables users to browse and discover relevant items from a large collection such as the Web of data. Existing faceted search solutions assume a precise information need, and thus optimise relevance, interestingness, and costs of fulfilling an information need. In this paper, we propose a complementary solution. Instead of assuming a search scenario (i.e., a user has a precise information need), our solution targets a browsing scenario (i.e., a user has a fuzzy need). We aim to support users in exploring an unknown collection of items, thereby allowing them to discover new or unfamiliar items of interest. Our approach comprises mechanisms for grouping facets and facet values and facet ranking. Via a task-based evaluation, we demonstrate that the proposed solution enables more effective browsing compared to the state-of-the-art, given fuzzy information needs.

Download: Media:SemanticFacetedSearch-TR-2011.pdf

Forschungsgruppe

Wissensmanagement

Forschungsgebiet

Information Retrieval, Semantische Suche

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 |ErsterAutorNachname=Wagner
 |ErsterAutorVorname=Andreas
+}}
+{{Publikation Author
+|Rank=2
+|Author=Günter Ladwig
+}}
+{{Publikation Author
+|Rank=3
+|Author=Duc Thanh Tran
 }}
 {{Misc
-|Title=Faceted Semantic Search
+|Title=Browsing-oriented Semantic Faceted Search
 |Year=2010
 |Month=Januar
@@ Zeile 10: / Zeile 18: @@
 }}
 {{Publikation Details
-|Abstract=Faceted search allows users to browse and discover relevant items from a large collection such as the Web. Given a large amount of facets, current solutions allow users to focus on a ranked list of facets. While state-of-the-art ranking mechanisms are either generic or assume that users are searching for specific items, the solution we propose targets fuzzy information needs. We want to support users in discovering new or unfamiliar items of interest. Thus, instead of supporting users in searching for specific items, we propose a ranking scheme that is oriented towards browsing and exploration. Also targeting effective browsing, we
+|Abstract=Faceted search enables users to browse and discover relevant items from a large collection such as the Web of data. Existing faceted search solutions assume a precise information need, and thus optimise relevance, interestingness, and costs of fulfilling an information need. In this paper, we propose a complementary solution. Instead of assuming a search scenario (i.e., a user has a precise information need), our solution targets a browsing scenario (i.e., a user has a fuzzy need). We aim to support users in exploring an unknown collection of items, thereby allowing them
-propose clustering and facet grouping mechanisms to allow users to uniformly browse facets and facet values. Via a task-based evaluation, we demonstrate that the proposed solution enables more effective browsing, when compared to the state-of-the-art that is focused on precise needs.
+to discover new or unfamiliar items of interest. Our approach comprises mechanisms for grouping facets and facet values and facet ranking. Via a task-based evaluation, we demonstrate that the proposed solution enables more effective browsing compared to the state-of-the-art, given fuzzy information needs.
-|Download=Paper-tr.pdf
+|Download=SemanticFacetedSearch-TR-2011.pdf
 |Forschungsgruppe=Wissensmanagement
 }}