Comparative evaluation of link-based approaches for candidate ranking in link-to-Wikipedia systems
|Comparative evaluation of link-based approaches for candidate ranking in link-to-Wikipedia systems|
|Author(s)||Garcia N.F., Fisteus J.A., Fernandez L.S.|
|Published in||Journal of Artificial Intelligence Research|
|Keyword(s)||Unknown (Extra: Semantics, Comparative evaluations, Context information, Empirical evaluations, Link informations, Link-based approach, Ranking approach, Ranking process, Wikipedia articles, Anchors)|
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Comparative evaluation of link-based approaches for candidate ranking in link-to-Wikipedia systems is a 2014 journal article written in English by Garcia N.F., Fisteus J.A., Fernandez L.S. and published in Journal of Artificial Intelligence Research.
In recent years, the task of automatically linking pieces of text (anchors) mentioned in a document to Wikipedia articles that represent the meaning of these anchors has received extensive research attention. Typically, link-to-Wikipedia systems try to find a set of Wikipedia articles that are candidates to represent the meaning of the anchor and, later, rank these candidates to select the most appropriate one. In this ranking process the systems rely on context information obtained from the document where the anchor is mentioned and/or from Wikipedia. In this paper we center our attention in the use of Wikipedia links as context information. In particular, we offer a review of several candidate ranking approaches in the state-of-the-art that rely on Wikipedia link information. In addition, we provide a comparative empirical evaluation of the different approaches on five different corpora: the TAC 2010 corpus and four corpora built from actual Wikipedia articles and news items. © 2014 AI Access Foundation. All rights reserved.
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