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Discovering Links Using Semantic Relatedness

Hoffart, Johannes and Bär, Daniel and Zesch, Torsten and Gurevych, Iryna
Geva, Shlomo and Kamps, Jaap and Trotman, Andrew (eds.) (2009):
Discovering Links Using Semantic Relatedness.
In: INEX 2009 Workshop Preproceedings, [Online-Edition: http://www.inex.otago.ac.nz/data/proceedings/INEX2009-prepro...],
[Conference or Workshop Item]

Abstract

We present our approaches for link discovery in document collections with or without existing links. In collections containing links, we discover links using measures of link anchor ranking based on existing links. In collections without links, we gather noun phrases as anchor candidates. To discover targets, we use a measure of semantic relatedness between texts. We find that semantic relatedness is useful to identify targets for ambiguous link anchors. In collections that contain no existing links, using only document titles as anchor candidates can be enhanced by using arbitrary noun phrases extracted from documents.

Item Type: Conference or Workshop Item
Erschienen: 2009
Editors: Geva, Shlomo and Kamps, Jaap and Trotman, Andrew
Creators: Hoffart, Johannes and Bär, Daniel and Zesch, Torsten and Gurevych, Iryna
Title: Discovering Links Using Semantic Relatedness
Language: English
Abstract:

We present our approaches for link discovery in document collections with or without existing links. In collections containing links, we discover links using measures of link anchor ranking based on existing links. In collections without links, we gather noun phrases as anchor candidates. To discover targets, we use a measure of semantic relatedness between texts. We find that semantic relatedness is useful to identify targets for ambiguous link anchors. In collections that contain no existing links, using only document titles as anchor candidates can be enhanced by using arbitrary noun phrases extracted from documents.

Title of Book: INEX 2009 Workshop Preproceedings
Uncontrolled Keywords: UKP_a_NLP4Wikis;UKP_p_WIKULU;UKP_s_DKPro_Similarity
Divisions: 20 Department of Computer Science
20 Department of Computer Science > Ubiquitous Knowledge Processing
Date Deposited: 31 Dec 2016 14:29
Official URL: http://www.inex.otago.ac.nz/data/proceedings/INEX2009-prepro...
Identification Number: TUD-CS-2010-0009
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