Identifying the topic of queries based on domain specify ontology
|Identifying the topic of queries based on domain specify ontology|
|Author(s)||ChienTa D.C., Thi T.P.|
|Published in||WIT Transactions on Information and Communication Technologies|
|Volume||58 VOL I|
|Keyword(s)||Domain ontology, Identifying topic, Information extraction (Extra: Artificial intelligence, Communication systems, Digital libraries, Information retrieval, Information technology, Learning algorithms, Natural language processing systems, Application systems, Domain ontologies, Domain-specific ontologies, Experimental evaluation, Identifying topic, Knowledge sources, NAtural language processing, Wikipedia, Data mining)|
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Identifying the topic of queries based on domain specify ontology is a 2014 conference paper written in English by ChienTa D.C., Thi T.P. and published in WIT Transactions on Information and Communication Technologies.
In order to identify the topic of queries, a large number of past researches have relied on lexicon-syntactic and handcrafted knowledge sources in Machine Learning and Natural Language Processing (NLP). Conversely, in this paper, we introduce the application system that detects the topic of queries based on domain-specific ontology. On this system, we work hard on building this domainspecific ontology, which is composed of instances automatically extracted from available resources such as Wikipedia, WordNet, and ACM Digital Library. The experimental evaluation with many cases of queries related to information technology area shows that this system considerably outperforms a matching and identifying approach.
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