DocumentCode
1774001
Title
Semantic ranking based on Computer Science Ontology weight
Author
Boonyoung, Thanyaporn ; Mingkhwan, Anirach
Author_Institution
Fac. of Inf. Technol., King Mongkut´s Univ. of Technol. North Bangkok, Bangkok, Thailand
fYear
2014
fDate
Sept. 29 2014-Oct. 1 2014
Firstpage
86
Lastpage
91
Abstract
Document Ranking retrieval systems are the top documents ordering and particularly appropriate for user´s query. Most existing assigned based on the information retrieval term frequency (tf) that appears in the document. Although the number of times that the term occurrence is more relevant, but not meant for rank documents according to their proximity to user´s query. So this paper, we presented a new document semantic ranking process for the semantic ranking that proposes a new weight of query term in the document based on Computer Science Ontology weight. The experimental results show that the new document similarity score between a user´s query and the paper suggests that the new measures were effectively ranked.
Keywords
computer science; query processing; computer science ontology weight; document ranking retrieval systems; document semantic ranking process; document similarity score; information retrieval term frequency; user query; Computational modeling; Computer science; Decision making; Information retrieval; Ontologies; Semantics; Vectors; Computer Science Ontology; Cosine Similarity; Semantic Ranking; Vector Space Model;
fLanguage
English
Publisher
ieee
Conference_Titel
Digital Information Management (ICDIM), 2014 Ninth International Conference on
Conference_Location
Phitsanulok
Type
conf
DOI
10.1109/ICDIM.2014.6991426
Filename
6991426
Link To Document