2012 ©
             Publication
Journal Publication
Title of Article A SEMANTIC QUESTION CLASSIFICATION FOR QUESTION ANSWERING SYSTEM USING LINKED OPEN DATA APPROACH 
Date of Acceptance 13 September 2019 
Journal
     Title of Journal JOURNAL OF THEORETICAL AND APPLIED INFORMATION TECHNOLOGY 
     Standard SCOPUS 
     Institute of Journal Little Lion Scientific 
     ISBN/ISSN  
     Volume 97 
     Issue 20 
     Month October
     Year of Publication 2019 
     Page 2293-2305 
     Abstract Semantic question answering (SQA) was the research study regarding the natural language processing. The purposes of this study were 1) to encourage the users to query via the computer with the semantic natural language, and 2) to obtain the concise, accurate, and relevant to the users needs. Recently, it was found that the research studies have encountered the problems with semantic communication, flexibility, and accuracy of processes, especially the process of question classification. It was considered the vital process of developing the semantic question answering system. Thus, this paper attempted to propose a semantic question classification for the question answering system using the linked open data approach. It proposed the problem-solving technique for question classification through semantic grammar rules derived from the questions based on principles of English grammar. Moreover, the linked open data, WordNet and DBpedia were implemented to solve the problems of words similarity and question classification through the question classification taxonomy consisting of six main classes and fifty subclasses as standards for question classification. Besides this, the dataset from the question sets of TREC with one thousand questions were also implemented. The evaluation indicated a high accuracy of question classification with the total scores of precision, recall, and F-measure, at 92.82%, 95.16%, and 93.97%, respectively. 
     Keyword Semantic Question Answering, Natural Language Processing, Question Classification, Linked Open Data, Semantic Web 
Author
577020027-9 Mr. KITTIPHONG SENGLOILUEAN [Main Author]
Science Doctoral Degree

Reviewing Status มีผู้ประเมินอิสระ 
Status ตีพิมพ์แล้ว 
Level of Publication นานาชาติ 
citation true 
Part of thesis true 
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