A graph based approach to estimating lexical cohesion
IIiX'08: Proceedings of the 2nd International Symposium on Information Interaction in Context
Please cite this item using this persistent URLhttp://hdl.handle.net/11693/26772
Traditionally, information retrieval systems rank documents according to the query terms they contain. However, even if a document may contain all query terms, this does not guarantee that it is relevant to the query. The query terms can occur together in the same document, but may have been used in different contexts, expressing separate topics. Lexical cohesion is a characteristic of natural language texts, which can be used to determine whether the query terms are used in the same context in the document. In this paper we make use of a graph-based approach to capture term contexts and estimate the level of lexical cohesion in a document. To evaluate the performance of our system, we compare it against two benchmark systems using three TREC document collections. Copyright 2008 ACM.
- Conference Paper 
Showing items related by title, author, creator and subject.
Soysal, E.; Cicekli I.; Baykal, N. (2010)This paper describes an information extraction system that extracts and converts the available information in free text Turkish radiology reports into a structured information model using manually created extraction rules ...
An analysis of manipulated information and respective alternative costs in information systems and in decision making structures Güvenen O.; Öztürk, M.H. (International Institute of Informatics and Systemics, IIIS, 2006)Today Information Technologies create base for the most important decision support systems for the practices in academia, business and politics. The effectiveness and success of operations that are supported by information ...
Altingövde İ.S.; Özel, S.A.; Ulusoy Ö.; Özsoyoğlu G.; Özsoyoğlu, Z.M. (Springer Verlag, 2001)This paper deals with the problem of modeling web information resources using expert knowledge and personalized user information, and querying them in terms of topics and topic relationships. We propose a model for web ...