2010
Similarity Query Postprocessing by Ranking
BUDÍKOVÁ, Petra; Michal BATKO and Pavel ZEZULABasic information
Original name
Similarity Query Postprocessing by Ranking
Name in Czech
Přeuspořádání výsledků podobnostních dotazů
Authors
Edition
Linz, 8th International Workshop on Adaptive Multimedia Retrieval, AMR'2010, 15 pp. 2010
Publisher
Johannes Kepler University
Other information
Language
English
Type of outcome
Proceedings paper
Field of Study
10201 Computer sciences, information science, bioinformatics
Country of publisher
Austria
Confidentiality degree
is not subject to a state or trade secret
Marked to be transferred to RIV
No
Organization unit
Faculty of Informatics
UT WoS
Keywords in English
ranking; content-based retrieval; metric space
Tags
Tags
International impact, Reviewed
Changed: 13/10/2010 14:58, RNDr. Michal Batko, Ph.D.
Abstract
In the original language
Current multimedia search technology is, especially in commercial applications, heavily based on text annotations. However, there are many applications such as image hosting web sites (e.g. Flickr or Picasa) where the text metadata are of poor quality in general. Searching such collections only by text gives usually rather unsatisfactory results. On the other hand, multimedia retrieval systems based purely on content can retrieve visually similar results but lag behind with the ability to grasp the semantics expressed by text annotations. In this paper, we propose various ranking techniques that can be transparently applied on any content-based retrieval system in order to improve the search results quality and user satisfaction. We demonstrate the usefulness of the approach on two large real-life datasets indexed by the MUFIN system. The improvement of the ranked results was evaluated by real users using an online survey.
Links
| GA201/09/0683, research and development project |
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| GP201/08/P507, research and development project |
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