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Version vom 15. Januar 2010, 10:28 Uhr
Veröffentlichung: 2010
Januar
Art der Veröffentlichung: Technical Report
BibTeX
Kurzfassung
The increasing amount of data on the Web bears potential for addressing complex
information needs more effectively. Instead of keyword search and browsing along
links between results, users can specify their needs in terms of complex queries and
obtain precise answers right away. However, browsing is also essential on the Web
of data as users might not always know a specific query language and more im-
portantly, might not know the data. Particularly in cases where the information
need is fuzzy, browsing is useful for exploring the data. Faceted search allows users
to browse along facets. However, work on faceted search so far has been focused
on search rather than browsing. In this paper, we propose a facet ranking scheme
that targets the browsing experience. When there are too many facets given, user
obtain a ranked list of facets, where the rank represents the facets’ browse-ability.
Furthermore, facets might be associated with a large amount of values. Also target-
ing browse-ability, we propose clustering mechanisms to decompose such facets into
more fine-grained sub-facets. By means of a task-based evaluation, we demonstrate
that the proposed solution enables more effective browsing, when compared to the
state of the art that is rather focused on search-ability.
Download: Media:FacetedSemanticSearchTR.pdf
Information Retrieval, Semantische Suche