In this paper, we investigate the combination of collaborative tagging and emergent semantics for improved data navigation and search. We propose to use visual features in addition to tags provided by users in order to discover new relationships between data. We show that our method is able to overcome some of the problems involved in navigating databases using tags only, such as synonymy or different languages, spelling mistakes, homonymy, or missing tags. On the other hand, image search based on visual features can be simplified substantially by the use of tags. We present technical details of our prototype system and show some preliminary results.
%0 Conference Paper
%1 Aurnhammer2006
%A Aurnhammer, Melanie
%A Hanappe, Peter
%A Steels, Luc
%B Proc. of the Collaborative Web Tagging Workshop (WWW '06
%D 2006
%K collaborative emergent_semantics homonymy image synonymy tagging visual
%T Integrating Collaborative Tagging and Emergent Semantics for Image Retrieval
%U http://www3.isrl.uiuc.edu/~junwang4/langev/localcopy/pdf/aurnhammer06semanticsWWW.pdf
%X In this paper, we investigate the combination of collaborative tagging and emergent semantics for improved data navigation and search. We propose to use visual features in addition to tags provided by users in order to discover new relationships between data. We show that our method is able to overcome some of the problems involved in navigating databases using tags only, such as synonymy or different languages, spelling mistakes, homonymy, or missing tags. On the other hand, image search based on visual features can be simplified substantially by the use of tags. We present technical details of our prototype system and show some preliminary results.
%Z Zus.Fassung: Tagging + feature extraction, um die Performance zu verbessern.
@inproceedings{Aurnhammer2006,
abstract = {In this paper, we investigate the combination of collaborative tagging and emergent semantics for improved data navigation and search. We propose to use visual features in addition to tags provided by users in order to discover new relationships between data. We show that our method is able to overcome some of the problems involved in navigating databases using tags only, such as synonymy or different languages, spelling mistakes, homonymy, or missing tags. On the other hand, image search based on visual features can be simplified substantially by the use of tags. We present technical details of our prototype system and show some preliminary results.
},
added-at = {2011-12-01T12:53:40.000+0100},
annote = {Zus.Fassung: Tagging + feature extraction, um die Performance zu verbessern.},
author = {Aurnhammer, Melanie and Hanappe, Peter and Steels, Luc},
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bdsk-url-1 = {http://www3.isrl.uiuc.edu/~junwang4/langev/localcopy/pdf/aurnhammer06semanticsWWW.pdf},
biburl = {https://www.bibsonomy.org/bibtex/257e38fe0dfb8da7096a06b6642d7ed8a/victorinostar},
booktitle = {Proc. of the Collaborative Web Tagging Workshop (WWW '06},
date-added = {2009-08-17 11:40:57 +0200},
date-modified = {2010-01-04 09:30:08 +0100},
interhash = {fe6ee22e5f84b706106cc2c3efcf6594},
intrahash = {57e38fe0dfb8da7096a06b6642d7ed8a},
keywords = {collaborative emergent_semantics homonymy image synonymy tagging visual},
rating = {1},
read = {Yes},
timestamp = {2011-12-01T12:53:40.000+0100},
title = {Integrating Collaborative Tagging and Emergent Semantics for Image Retrieval},
url = {http://www3.isrl.uiuc.edu/~junwang4/langev/localcopy/pdf/aurnhammer06semanticsWWW.pdf},
urldate = {23.5.2008},
year = 2006
}