MIaS: Math-Aware Retrieval in Digital Mathematical Libraries
This addresses the need for effective math information retrieval in STEM fields, offering a practical solution for digital mathematical libraries.
The paper tackles the problem of retrieving mathematical formulae in digital libraries by developing MIaS, a math-aware retrieval system that outperforms conventional IR methods, as demonstrated by winning the NTCIR-11 Math-2 task.
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.