Binary vector transformation of math formula for mathematical information retrieval

Amarnath Pathak, Partha Pakray, Alexander Gelbukh

Research output: Contribution to journalArticlepeer-review

11 Scopus citations

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.

Original languageEnglish
Pages (from-to)4685-4695
Number of pages11
JournalJournal of Intelligent and Fuzzy Systems
Volume36
Issue number5
DOIs
StatePublished - 2019

Keywords

  • Binary vector transformation
  • Bit position information table
  • Math formula search
  • Mathematical information retrieval
  • Precision
  • Scientific document retrieval

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