IRAug 8, 2015

Combining Text and Formula Queries in Math Information Retrieval: Evaluation of Query Results Merging Strategies

arXiv:1508.01929v117 citations
Originality Synthesis-oriented
AI Analysis

This work addresses the challenge of retrieving math documents for researchers and practitioners, but it is incremental as it adapts existing methods to a specific domain.

The paper tackled the problem of combining text and mathematical formulae in math information retrieval queries, showing that applying techniques from textual query processing, such as striping and merging partial results, leads to cutting-edge performance with improvements measured by metrics like Bpref.

Specific to Math Information Retrieval is combining text with mathematical formulae both in documents and in queries. Rigorous evaluation of query expansion and merging strategies combining math and standard textual keyword terms in a query are given. It is shown that techniques similar to those known from textual query processing may be applied in math information retrieval as well, and lead to a cutting edge performance. Striping and merging partial results from subqueries is one technique that improves results measured by information retrieval evaluation metrics like Bpref.

Foundations

The foundational work for this paper's niche, ranked by how specifically the neighbourhood builds on it — not by global fame.

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