NDLI: Improving key concept extraction using word association measurement

Content Provider	IEEE Xplore Digital Library
Author	Doan, Phuoc Thi Hong Arch-int, Ngamnij Arch-int, Somjit
Copyright Year	2015
Description	Author affiliation: Department of Computer Science - Faculty of Science -Khon Kaen University, Khon Kaen - Thailand (Doan, Phuoc Thi Hong; Arch-int, Ngamnij; Arch-int, Somjit)
Abstract	Ontologies play a very important role in information exchange and sharing, and are typically constructed by human experts. However, this process is very costly in both time and effort. Given this, there is a need for automated ontology construction from various knowledge (such as text files). A key challenge of automated ontology learning from text is to extract key concepts, which are relevant to the domain, from the documents. Existing approaches typically require a large set of training data with prior domain-specific knowledge. However, it is not always possible to provide such knowledge and trained data sets. To overcome this issue, we present a method to obtain key concepts from unstructured texts by using the word association measure and statistical knowledge. To demonstrate the efficiency of our method in comparison with a state-of-the-art method, extensive experiments, which employed two real-world datasets, were performed. The obtained results indicate that our method achieves better accuracy than the state of the art method for 3% to 10% in case of not having domain-specific knowledge. The results are more efficient if there are many noun phrases (in data sets) whose number of words is large.
Starting Page	403
Ending Page	407
File Size	246851
Page Count	5
File Format	PDF
e-ISBN	9781467378635
DOI	10.1109/ICITEED.2015.7408980
Language	English
Publisher	Institute of Electrical and Electronics Engineers, Inc. (IEEE)
Publisher Date	2015-10-29
Publisher Place	Thailand
Access Restriction	Subscribed
Rights Holder	Institute of Electrical and Electronics Engineers, Inc. (IEEE)
Subject Keyword	Weight measurement Terminology Ontology Ontology learning Medical services Ontologies Feature extraction Information technology Word association Key concept extraction Pragmatics
Content Type	Text
Resource Type	Article

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1	Ministry of Education (GoI), Department of Higher Education	Sanctioning Authority	https://www.education.gov.in/ict-initiatives
2	Indian Institute of Technology Kharagpur	Host Institute of the Project: The host institute of the project is responsible for providing infrastructure support and hosting the project	https://www.iitkgp.ac.in
3	National Digital Library of India Office, Indian Institute of Technology Kharagpur	The administrative and infrastructural headquarters of the project	Dr. B. Sutradhar bsutra@ndl.gov.in
4	Project PI / Joint PI	Principal Investigator and Joint Principal Investigators of the project	Dr. B. Sutradhar bsutra@ndl.gov.in Prof. Saswat Chakrabarti will be added soon
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