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An exploration of learning to link with wikipedia: Features, methods and training collection
Abstract We describe our participation in the Link-We describe our participation in the Link-the-Wiki track at INEX 2009. We apply machine learning methods to the anchor-to-best-entry-point task and explore the impact of the following aspects of our approaches: features, learning methods as well as the collection used for training the models. We find that a learning to rank-based approach and a binary classification approach do not differ a lot. The new Wikipedia collection which is of larger size and which has more links than the collection previously used, provides better training material for learning our models. In addition, a heuristic run which combines the two intuitively most useful features outperforms machine learning based runs, which suggests that a further analysis and selection of features is necessary.is and selection of features is necessary.
Abstractsub We describe our participation in the Link-We describe our participation in the Link-the-Wiki track at INEX 2009. We apply machine learning methods to the anchor-to-best-entry-point task and explore the impact of the following aspects of our approaches: features, learning methods as well as the collection used for training the models. We find that a learning to rank-based approach and a binary classification approach do not differ a lot. The new Wikipedia collection which is of larger size and which has more links than the collection previously used, provides better training material for learning our models. In addition, a heuristic run which combines the two intuitively most useful features outperforms machine learning based runs, which suggests that a further analysis and selection of features is necessary.is and selection of features is necessary.
Bibtextype inproceedings  +
Doi 10.1007/978-3-642-14556-8_32  +
Has author He J. + , Maarten de Rijke +
Has extra keyword Binary Classification Approach + , Learning methods + , Learning to rank + , Machine learning methods + , Machine learning + , Training material + , Wikipedia + , Learning systems + , Markup languages + , XML + , Feature extraction +
Isbn 3642145558; 9783642145551  +
Language English +
Number of citations by publication 0  +
Number of references by publication 0  +
Pages 324–330  +
Published in Lecture Notes in Computer Science +
Title An exploration of learning to link with wikipedia: Features, methods and training collection +
Type conference paper  +
Volume 6203 LNCS  +
Year 2010 +
Creation dateThis property is a special property in this wiki. 6 November 2014 23:29:42  +
Categories Publications without keywords parameter  + , Publications without license parameter  + , Publications without remote mirror parameter  + , Publications without archive mirror parameter  + , Publications without paywall mirror parameter  + , Conference papers  + , Publications without references parameter  + , Publications  +
Modification dateThis property is a special property in this wiki. 6 November 2014 23:29:42  +
DateThis property is a special property in this wiki. 2010  +
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