Paper Info
Title
Co-active intelligence for image retrieval
Abstract
Lexical ambiguity in query-based image retrieval is an immemorial problem which has seemingly resisted all countermeasures. In this paper we introduce a methodology that expresses the users of a system and their navigational behaviour as the paramount resource for resolving query term ambiguity. Mass user consensus is modelled within a multi-dimensional feature space and evaluated through cluster analysis. This technique resolves query term ambiguity in a wholly democratic and dynamic fashion, in contrast to the brittle centralised models of contemporary word sense classification systems. The simple approach contained herein leads to several interesting emergent properties.
Year
DOI
Venue
2005
10.1145/1101149.1101273
ACM Multimedia 2001
Keywords
Field
DocType
co-active intelligence,dynamic fashion,contemporary word sense classification,brittle centralised model,mass user consensus,immemorial problem,lexical ambiguity,query term ambiguity,image retrieval,interesting emergent property,multi-dimensional feature space,cluster analysis,clustering,feature space,ir,classification system,word sense,emergent properties
Computer vision,Feature vector,Information retrieval,Computer science,Image retrieval,Artificial intelligence,Word sense,Cluster analysis,Ambiguity,Visual Word
Conference
ISBN
Citations 
PageRank 
1-59593-044-2
13
0.75
References 
Authors
12
3
Name
Order
Citations
PageRank
Mark Truran128614.43
James Goulding27012.23
Helen Ashman376766.74