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 :
بازگشت