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A New LCS-Neutrosophic Similarity Measure for Text Information Retrieval

A New LCS-Neutrosophic Similarity Measure for Text Information Retrieval

Misturah Adunni Alaran, AbdulAkeem Adesina Agboola, Adio Taofiki Akinwale, Olusegun Folorunso
Copyright: © 2020 |Pages: 23
ISBN13: 9781799825555|ISBN10: 1799825558|ISBN13 Softcover: 9781799825562|EISBN13: 9781799825579
DOI: 10.4018/978-1-7998-2555-5.ch012
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MLA

Alaran, Misturah Adunni, et al. "A New LCS-Neutrosophic Similarity Measure for Text Information Retrieval." Neutrosophic Sets in Decision Analysis and Operations Research, edited by Mohamed Abdel-Basset and Florentin Smarandache, IGI Global, 2020, pp. 258-280. https://doi.org/10.4018/978-1-7998-2555-5.ch012

APA

Alaran, M. A., Agboola, A. A., Akinwale, A. T., & Folorunso, O. (2020). A New LCS-Neutrosophic Similarity Measure for Text Information Retrieval. In M. Abdel-Basset & F. Smarandache (Eds.), Neutrosophic Sets in Decision Analysis and Operations Research (pp. 258-280). IGI Global. https://doi.org/10.4018/978-1-7998-2555-5.ch012

Chicago

Alaran, Misturah Adunni, et al. "A New LCS-Neutrosophic Similarity Measure for Text Information Retrieval." In Neutrosophic Sets in Decision Analysis and Operations Research, edited by Mohamed Abdel-Basset and Florentin Smarandache, 258-280. Hershey, PA: IGI Global, 2020. https://doi.org/10.4018/978-1-7998-2555-5.ch012

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Abstract

The reality of human existence and their interactions with various things that surround them reveal that the world is imprecise, incomplete, vague, and even sometimes indeterminate. Neutrosophic logic is the only theory that attempts to unify all previous logics in the same global theoretical framework. Extracting data from a similar environment is becoming a problem as the volume of data keeps growing day-in and day-out. This chapter proposes a new neutrosophic string similarity measure based on the longest common subsequence (LCS) to address uncertainty in string information search. This new method has been compared with four other existing classical string similarity measure using wordlist as data set. The analyses show the performance of proposed neutrosophic similarity measure to be better than the existing in information retrieval task as the evaluation is based on precision, recall, highest false match, lowest true match, and separation.

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