Article,
Using TF-ISF with Local Context to Generate an Owl Document Representation for Sentence Retrieval
Computer Science & Engineering: An International Journal (CSEIJ), 05 (05): 01-15 (October 2015)
DOI: 10.5121/cseij.2015.5501
Abstract
In this paper we combine our previous research in the field of Semantic web, especially ontology learning and population with Sentence retrieval. To do this we developed a new approach to sentence retrieval modifying our previous TF-ISF method which uses local context information to take into account only document level information. This is quite a new approach to sentence retrieval, presented for the first time in this paper and also compared to the existing methods that use information from whole document collection. Using this approach and developed methods for sentence retrieval on a document level it is possible to assess the relevance of a sentence by using only the information from the retrieved sentence’s document and to define a document level OWL representation for sentence retrieval that can be automatically populated. In this way the idea of Semantic Web through automatic and semi-automatic extraction of additional information from existing web resources is supported. Additional information is formatted in OWL document containing document sentence relevance for sentence retrieval.
