Enriching domain concepts with qualitative attributes : a text mining based approach
Joint Authors
Behera, Niyati Kumari
Mahalakshmi, Guruvayur Suryanarayanan
Source
The International Arab Journal of Information Technology
Issue
Vol. 17, Issue 6 (30 Nov. 2020), pp.916-925, 10 p.
Publisher
Zarqa University Deanship of Scientific Research
Publication Date
2020-11-30
Country of Publication
Jordan
No. of Pages
10
Main Subjects
Information Technology and Computer Science
Abstract EN
ttributes, whether qualitative or non-qualitative are the formal description of any real-world entity and are crucial in modern knowledge representation models like ontology.
Though ample evidence for the amount of research done for mining non-qualitative attributes (like part-of relation) extraction from text as well as the Web is available in the wealth of literature, on the other side limited research can be found relating to qualitative attribute (i.e., size, color, taste etc.,) mining.
Herein this research article an analytical framework has been proposed to retrieve qualitative attribute values from unstructured domain text.
The research objective covers two aspects of information retrieval (1) acquiring quality values from unstructured text and (2) then assigning attribute to them by comparing the Google derived meaning or context of attributes as well as quality value (adjectives).
The goal has been accomplished by using a framework which integrates Vector Space Modelling (VSM) with a probabilistic Multinomial Naive Bayes (MNB) classifier.
Performance Evaluation has been carried out on two data sets (1) HeiPLAS Development Data set (106 adjective-noun exemplary phrases) and (2) a text data set in Medicinal Plant Domain (MPD).
System is found to perform better with probabilistic approach compared to the existing pattern-based framework in the state of art.
American Psychological Association (APA)
Behera, Niyati Kumari& Mahalakshmi, Guruvayur Suryanarayanan. 2020. Enriching domain concepts with qualitative attributes : a text mining based approach. The International Arab Journal of Information Technology،Vol. 17, no. 6, pp.916-925.
https://search.emarefa.net/detail/BIM-1433885
Modern Language Association (MLA)
Behera, Niyati Kumari& Mahalakshmi, Guruvayur Suryanarayanan. Enriching domain concepts with qualitative attributes : a text mining based approach. The International Arab Journal of Information Technology Vol. 17, no. 6 (Nov. 2020), pp.916-925.
https://search.emarefa.net/detail/BIM-1433885
American Medical Association (AMA)
Behera, Niyati Kumari& Mahalakshmi, Guruvayur Suryanarayanan. Enriching domain concepts with qualitative attributes : a text mining based approach. The International Arab Journal of Information Technology. 2020. Vol. 17, no. 6, pp.916-925.
https://search.emarefa.net/detail/BIM-1433885
Data Type
Journal Articles
Language
English
Notes
Includes bibliographical references : p. 923-925
Record ID
BIM-1433885