MIaS: Math-Aware Retrieval in Digital Mathematical Libraries

TL;DR

MIaS is a new math-aware retrieval system for digital mathematical libraries that effectively combines text and formula search, demonstrated by its success in the NTCIR-11 Math-2 challenge.

Contribution

The paper introduces MIaS, an open-source system that integrates formula preprocessing with full-text search for improved mathematical information retrieval.

Findings

MIaS is efficient and fast.

MIaS outperforms existing systems in math retrieval quality.

MIaS won the NTCIR-11 Math-2 task.

Abstract

Digital mathematical libraries (DMLs) such as arXiv, Numdam, and EuDML contain mainly documents from STEM fields, where mathematical formulae are often more important than text for understanding. Conventional information retrieval (IR) systems are unable to represent formulae and they are therefore ill-suited for math information retrieval (MIR). To fill the gap, we have developed, and open-sourced the MIaS MIR system. MIaS is based on the full-text search engine Apache Lucene. On top of text retrieval, MIaS also incorporates a set of tools for preprocessing mathematical formulae. We describe the design of the system and present speed, and quality evaluation results. We show that MIaS is both efficient, and effective, as evidenced by our victory in the NTCIR-11 Math-2 task.