DocumentCode :
3530825
Title :
Principles of Information Filtering in Metric Spaces
Author :
Ciaccia, Paolo ; Patella, Marco
Author_Institution :
DEIS, Univ. di Bologna, Bologna, Italy
fYear :
2009
fDate :
29-30 Aug. 2009
Firstpage :
99
Lastpage :
106
Abstract :
The traditional problem of similarity search requires to find, within a set of points, those that are closer to a query point q, according to a distance function d. In this paper we introduce the novel problem of metric filtering: in this scenario, each data point xi possesses its own distance function di and the task is to find those points that are close enough, according to di, to a query point q. This minor difference in the problem formulation introduces a series of challenges from the point of view of efficient evaluation. We provide basic definitions and alternative pivot-based resolution strategies, presenting results from a preliminary experimentation that show how the proposed solutions are indeed effective in reducing evaluation costs.
Keywords :
information filtering; query processing; distance function; information filtering; metric filtering; metric space; pivot-based resolution strategy; query point; similarity search; Content based retrieval; Costs; Extraterrestrial measurements; Helium; Information filtering; Information filters; Information retrieval; Multimedia databases; Search problems; Spatial databases;
fLanguage :
English
Publisher :
ieee
Conference_Titel :
Similarity Search and Applications, 2009. SISAP '09. Second International Workshop on
Conference_Location :
Prague
Print_ISBN :
978-0-7695-3765-8
Type :
conf
DOI :
10.1109/SISAP.2009.11
Filename :
5271947
Link To Document :
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