Math Indexer and Searcher under the Hood: History and Development of a Winning Strategy

This paper describes and summarizes experience of Masaryk University Math Information Retrieval team (MIRMU) with the mathematical search developed and performed for the NTCIR-11 Math-2 Task. Our approach is the similarity search based on canonicalized MathML and second generation of scalable full text search engine Math Indexer and Searcher (MIaS) with attested state-of-the-art information retrieval techniques like query expansion. The capability of MIaS system in terms of math query notation, normalization and combining math with textual query tokens was deployed by submitting multiple runs with four query notations provided, and with results merged from multiple queries. The analysis of the evaluation results shows that the system performs best using TEX queries that are translated and canonicalized to Content MathML, where MIaS ranked as #1 for all metrics returning very relevant results.