Paper Info
Title
Exploiting locality of Wikipedia links in entity ranking
Abstract
Information retrieval from web and XML document collections ever more focused on returning entities instead of web pages or XML elements. There are many research fields involving named entities; one such field is known as entity ranking, where one goal is to rank entities in response to a query supported with a short list of entity examples. In this paper, we describe our approach to ranking entities from the Wikipedia XML document collection. Our approach utilises the known categories and the link structure of Wikipedia, and more importantly, exploits link co-occurrences to improve the effectiveness of entity ranking. Using the broad context of a full Wikipedia page as a baseline, we evaluate two different algorithms for identifying narrow contexts around the entity examples: one that uses predefined types of elements such as paragraphs, lists and tables; and another that dynamically identifies the contexts by utilising the underlying XML document structure. Our experiments demonstrate that the locality of Wikipedia links can be exploited to significantly improve the effectiveness of entity ranking.
Year
DOI
Venue
2008
10.1007/978-3-540-78646-7_25
ECIR
Keywords
Field
DocType
exploiting locality,known category,xml element,entity example,entity ranking,wikipedia xml document collection,ranking entity,xml document collection,wikipedia link,underlying xml document structure,full wikipedia page,web pages,xml document,information retrieval,wikipedia,xml,document structure
Entity linking,Data mining,World Wide Web,Information retrieval,Well-formed document,XML,Ranking,Computer science,XML validation,Document Structure Description,XML Catalog,Document type definition
Conference
Volume
ISSN
ISBN
4956
0302-9743
3-540-78645-7
Citations 
PageRank 
References 
24
1.19
12
Authors
3
Name
Order
Citations
PageRank
Jovan Pehcevski119913.72
Anne-Marie Vercoustre233181.83
James A. Thom3622182.05