Preliminary Results in Tag Disambiguation using DBpedia
Preliminary Results in Tag Disambiguation using DBpedia
The availability of tag-based user-generated content for a variety of Web resources (music, photos, videos, text, etc.) has largely increased in the last years. Users can assign tags freely and then use them to share and retrieve information. However, tag-based sharing and retrieval is not optimal due to the fact that tags are plain text labels without an explicit or formal meaning, and hence polysemy and synonymy should be dealt with appropriately. To ameliorate these problems, we propose a context-based tag disambiguation algorithm that selects the meaning of a tag among a set of candidate DBpedia entries, using a common information retrieval similarity measure. The most similar DBpedia entry is selected as the one representing the meaning of the tag. We describe and analyze some preliminary results, and discuss about current challenges in this area.
Garcia, Andres
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Szomszor, Martin
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Alani, Harith
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Corcho, Oscar
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September 2009
Garcia, Andres
3b79142a-768e-4480-aca5-f9d0505f932b
Szomszor, Martin
c797d2c4-7fd3-45f5-9aa6-474faf550786
Alani, Harith
70cdbdce-1494-44c2-9dae-65d82bf7e991
Corcho, Oscar
f5a436c8-9c9e-4e97-af05-aebf39bb7e5d
Garcia, Andres, Szomszor, Martin, Alani, Harith and Corcho, Oscar
(2009)
Preliminary Results in Tag Disambiguation using DBpedia.
Knowledge Capture (K-Cap'09) - First International Workshop on Collective Knowledge Capturing and Representation - CKCaR'09, Redondo Beach, California, United States.
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Conference or Workshop Item
(Paper)
Abstract
The availability of tag-based user-generated content for a variety of Web resources (music, photos, videos, text, etc.) has largely increased in the last years. Users can assign tags freely and then use them to share and retrieve information. However, tag-based sharing and retrieval is not optimal due to the fact that tags are plain text labels without an explicit or formal meaning, and hence polysemy and synonymy should be dealt with appropriately. To ameliorate these problems, we propose a context-based tag disambiguation algorithm that selects the meaning of a tag among a set of candidate DBpedia entries, using a common information retrieval similarity measure. The most similar DBpedia entry is selected as the one representing the meaning of the tag. We describe and analyze some preliminary results, and discuss about current challenges in this area.
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CKCaR09-final.pdf
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Published date: September 2009
Venue - Dates:
Knowledge Capture (K-Cap'09) - First International Workshop on Collective Knowledge Capturing and Representation - CKCaR'09, Redondo Beach, California, United States, 2009-09-01
Organisations:
Web & Internet Science
Identifiers
Local EPrints ID: 267792
URI: http://eprints.soton.ac.uk/id/eprint/267792
PURE UUID: ffd94268-5987-446f-b038-77bbed56c20e
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Date deposited: 21 Aug 2009 14:32
Last modified: 14 Mar 2024 08:58
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Contributors
Author:
Andres Garcia
Author:
Martin Szomszor
Author:
Harith Alani
Author:
Oscar Corcho
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