Please use this identifier to cite or link to this item: http://hdl.handle.net/10397/5552
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Title: Aggregating skip bigrams into key phrase-based vector space model for web person disambiguation
Authors: Xu, J
Lu, Q 
Liu, Z
Issue Date: Sep-2012
Source: In J. Jancsary (ed), Empirical methods in natural language processing : proceedings of the Conference on Natural Language Processing 2012, p. 108-117
Abstract: Web Person Disambiguation (WPD) is often done through clustering of web documents to identify the different namesakes for a given name. This paper presents a clustering algorithm using key phrases as the basic feature. However, key phrases are used in two different forms to represent the document as well context information surround the name mentions in a document. In using the vector space model, key phrases extracted from the documents are used as document representation. Context information of name mentions is represented by skip bigrams of the key phrase sequences surrounding the name mentions. The two components are then aggregated into the vector space model for clustering Experiments on the WePS2 datasets show that the proposed approach achieved comparable results with the top 1 system. It indicates that key phrases can be a very effective feature for WPD both at the document level and at the sentential level near the name mentions.
Publisher: ÖGAI = Austrian Society for Artificial Intelligence
ISBN: 3-85027-005-X Online/CD-ROM-Ausgabe
Description: The 11th Conference on Natural Language Processing (KONVENS) was organized by ÖGAI and was hosted on September 19-21, 2012 in Vienna.
Rights: © 2012 ÖGAI
Alle Rechte, auch die des auszugsweisen Nachdrucks, vorbehalten. Die Rechte bezüglich der individuellen Beiträge verbleiben bei den Autoren.
© 2012 ÖGAI
All rights, even the partial reprint, reserved. The rights concerning the individual contributions remain with the authors.
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