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Issue title: Special Section: Intelligent and Fuzzy Systems applied to Language & Knowledge Engineering
Guest editors: David Pinto and Vivek Singh
Article type: Research Article
Authors: Pathak, Amarnatha | Pakray, Parthab; * | Gelbukh, Alexanderc
Affiliations: [a] Department of Computer Science and Engineering, National Institute of Technology Mizoram, India | [b] Department of Computer Science and Engineering, National Institute of Technology Silchar, India | [c] Instituto Politécnico Nacional, Center for Computing Research (CIC), Mexico
Correspondence: [*] Corresponding author. P. Pakray. E-mail: [email protected].
Abstract: Scientific documents, which are majorly constituted of math formulae, form a primary source of scientific and technical information. However, the indexing and the search processes of conventional search engines barely account for mathematical contents of such documents. Though the recent past has witnessed a surge in number of Mathematical Information Retrieval (MIR) systems intending to retrieve math formulae from scientific documents, the low values of their evaluation measures are indicative of the scope for improvement. To cope with the challenges of MIR, and to further the performance of state-of-the-art systems, a novel approach, called Binary Vector Transformation of Math Formula (BVTMF), is introduced. The implemented system extracts MathML formulae from the documents, preprocesses them, and renders them into fairly large-sized binary vectors (vectors of ‘0’s and ‘1’s). Generated formula vector is representative of the information content of corresponding formula. For indexing and searching text contents, the system relies on Apache Lucene. Text and math search results retrieved by independent text and math sub-systems are re-ranked to prioritize the results containing text as well as math components of the user query. Quality of the retrieved search results and appreciable values of the evaluation measures substantiate competence of the proposed approach.
Keywords: Mathematical information retrieval, binary vector transformation, math formula search, scientific document retrieval, precision, bit position information table
DOI: 10.3233/JIFS-179018
Journal: Journal of Intelligent & Fuzzy Systems, vol. 36, no. 5, pp. 4685-4695, 2019
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