DocumentCode
2728179
Title
Measuring Semantic Similarity between Named Entities by Searching the Web Directory
Author
Liu, Jiahui ; Birnbaum, Larry
fYear
2007
fDate
2-5 Nov. 2007
Firstpage
461
Lastpage
465
Abstract
The importance of named entities in information retrieval and knowledge management has recently brought interest in characterizing semantic relationships between entities. In this paper, we propose a method for measuring semantic similarity, an important type of semantic relationship, between entities. The method is based on Google Directory, a search interface to the Open Directory Project. Via the search engine, we can locate the web pages relevant to an entity and automatically create a profile of the entity according to the directory assignments of its web pages, which capture various features of the entity. Using their profiles, the semantic similarity between entities can be measured in different dimensions. We apply the semantic similarity measurement to two knowledge acquisition tasks: thesaurus construction of entities and fine grained categorization of entities. Our experiments demonstrate that the proposed method works effectively in these two tasks.
Keywords
Humans; Information retrieval; Knowledge acquisition; Knowledge engineering; Knowledge management; Particle measurements; Search engines; Thesauri; USA Councils; Web pages;
fLanguage
English
Publisher
ieee
Conference_Titel
Web Intelligence, IEEE/WIC/ACM International Conference on
Conference_Location
Fremont, CA
Print_ISBN
978-0-7695-3026-0
Type
conf
DOI
10.1109/WI.2007.70
Filename
4427135
Link To Document