D 2010

Similarity Query Postprocessing by Ranking

BUDÍKOVÁ, Petra, Michal BATKO and Pavel ZEZULA

Basic information

Original name

Similarity Query Postprocessing by Ranking

Name in Czech

Přeuspořádání výsledků podobnostních dotazů

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

Stať ve sborníku

Field of Study

10201 Computer sciences, information science, bioinformatics

Country of publisher

Austria

Confidentiality degree

není předmětem státního či obchodního tajemství

Organization unit

Faculty of Informatics

UT WoS

000306440900012

Keywords in English

ranking; content-based retrieval; metric space

Tags

Tags

International impact, Reviewed
Změněno: 13/10/2010 14:58, RNDr. Michal Batko, Ph.D.

Abstract

V originále

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
Name: Vyhledávání v rozsáhlých multimediálních databázích
Investor: Czech Science Foundation, Similarity Searching in Very Large Multimedia Databases
GP201/08/P507, research and development project
Name: Komplexní podobnostní dotazy nad rozsáhlými objemy dat
Investor: Czech Science Foundation, Complex similarity searching in very large data collections