A k-Nearest-Neighbour Method for Classifying Web Search Results with Data in Folksonomies
A k-Nearest-Neighbour Method for Classifying Web Search Results with Data in Folksonomies
Traditional Web search engines mostly adopt a keyword-based approach. When the keyword submitted by the user is ambiguous, search result usually consists of documents related to various meanings of the keyword, while the user is probably interested in only one of them. In this paper we attempt to provide a solution to this problem using a k-nearest-neighbour approach to classify documents returned by a search engine, by building classifiers using data collected from collaborative tagging systems. Experiments on search results returned by Google show that our method is able to classify the documents returned with high precision.
web search, classification, folksonomy, tagging
70-76
Au Yeung, Ching Man
c83390b1-d3a1-459e-8f09-01c81576e066
Gibbins, Nicholas
98efd447-4aa7-411c-86d1-955a612eceac
Shadbolt, Nigel
5c5acdf4-ad42-49b6-81fe-e9db58c2caf7
9 December 2008
Au Yeung, Ching Man
c83390b1-d3a1-459e-8f09-01c81576e066
Gibbins, Nicholas
98efd447-4aa7-411c-86d1-955a612eceac
Shadbolt, Nigel
5c5acdf4-ad42-49b6-81fe-e9db58c2caf7
Au Yeung, Ching Man, Gibbins, Nicholas and Shadbolt, Nigel
(2008)
A k-Nearest-Neighbour Method for Classifying Web Search Results with Data in Folksonomies.
2008 IEEE/WIC/ACM International Conference on Web Intelligence and Intelligent Agent Technology, Sydney, Australia.
09 - 12 Dec 2008.
.
Record type:
Conference or Workshop Item
(Paper)
Abstract
Traditional Web search engines mostly adopt a keyword-based approach. When the keyword submitted by the user is ambiguous, search result usually consists of documents related to various meanings of the keyword, while the user is probably interested in only one of them. In this paper we attempt to provide a solution to this problem using a k-nearest-neighbour approach to classify documents returned by a search engine, by building classifiers using data collected from collaborative tagging systems. Experiments on search results returned by Google show that our method is able to classify the documents returned with high precision.
Text
wi08_websearch_presentation.pdf
- Other
Text
cmauyeung-WebSearchFolksonomy.pdf
- Version of Record
More information
Published date: 9 December 2008
Additional Information:
Event Dates: 9-12 December 2008
Venue - Dates:
2008 IEEE/WIC/ACM International Conference on Web Intelligence and Intelligent Agent Technology, Sydney, Australia, 2008-12-09 - 2008-12-12
Keywords:
web search, classification, folksonomy, tagging
Organisations:
Web & Internet Science
Identifiers
Local EPrints ID: 266991
URI: http://eprints.soton.ac.uk/id/eprint/266991
PURE UUID: 7609459e-5087-41d2-bc28-d539afb7d764
Catalogue record
Date deposited: 21 Dec 2008 13:43
Last modified: 15 Mar 2024 02:59
Export record
Contributors
Author:
Ching Man Au Yeung
Author:
Nicholas Gibbins
Author:
Nigel Shadbolt
Download statistics
Downloads from ePrints over the past year. Other digital versions may also be available to download e.g. from the publisher's website.
View more statistics