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Integrating document features for entity ranking

Zhu, Jianhan; Song, Dawei and Rüger, Stefan (2008). Integrating document features for entity ranking. In: Focused Access to XML Documents, pp. 336–347.

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The Knowledge Media Institute of the Open University participated in the entity ranking and entity list completion tasks of the Entity Ranking Track in INEX 2007. In both the entity ranking and entity list completion tasks, we have considered document features in addition to a basic document content based relevance model. These document features include categorizations of documents, relevance of category names to the query, and hierarchical relations between categories. Furthermore, based on our TREC2006 and 2007 expert search approach, we applied a co-occurrence based entity association discovery model to the two tasks based on the assumption that relevant entities often co-occur with query terms or given relevant entities in documents. Our initial experimental results show that, by considering the predefined category, its children and grandchildren in the document content based relevance model, the performance of our entity ranking approach can be significantly improved. Consideration of the predefined category’s parents, a category name based relevance model, and the co-occurrence model is not shown to be helpful in entity ranking and list completion, respectively.

Item Type: Conference or Workshop Item
Copyright Holders: 2008 Springer-Verlag Berlin Heidelberg
ISSN: 0302-9743
Extra Information: Published in Lecture Notes in Computer Science, 2008, Volume 4862/2008, 336-347
Keywords: entity ranking; list completion; entity retrieval; categories
Academic Unit/School: Faculty of Science, Technology, Engineering and Mathematics (STEM) > Knowledge Media Institute (KMi)
Faculty of Science, Technology, Engineering and Mathematics (STEM)
Faculty of Science, Technology, Engineering and Mathematics (STEM) > Computing and Communications
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Item ID: 25890
Depositing User: Kay Dave
Date Deposited: 04 Jan 2011 12:29
Last Modified: 07 Dec 2018 09:47
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