SOJKA, Petr, Michal RŮŽIČKA and Vít NOVOTNÝ. MIaS: Math-Aware Retrieval in Digital Mathematical Libraries. In Proceedings of the 27th ACM International Conference on Information and Knowledge Management (CIKM '18). Torino, Italy: Association for Computing Machinery, 2018. p. 1923-1926, 4 pp. ISBN 978-1-4503-6014-2. doi:10.1145/3269206.3269233.
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Basic information
Original name MIaS: Math-Aware Retrieval in Digital Mathematical Libraries
Authors SOJKA, Petr (203 Czech Republic, guarantor, belonging to the institution), Michal RŮŽIČKA (203 Czech Republic, belonging to the institution) and Vít NOVOTNÝ (203 Czech Republic, belonging to the institution).
Edition Torino, Italy, Proceedings of the 27th ACM International Conference on Information and Knowledge Management (CIKM '18), p. 1923-1926, 4 pp. 2018.
Publisher Association for Computing Machinery
Other information
Original language English
Type of outcome Proceedings paper
Field of Study 10201 Computer sciences, information science, bioinformatics
Country of publisher Italy
Confidentiality degree is not subject to a state or trade secret
Publication form electronic version available online
WWW DOI Postprint
RIV identification code RIV/00216224:14330/18:00100679
Organization unit Faculty of Informatics
ISBN 978-1-4503-6014-2
UT WoS 000455712300261
Keywords (in Czech) vyhledávání matematiky; DML; EuDML; digitální matematické knihovny
Keywords in English Math Information Retrieval; DML; EuDML; Digital Mathematical Libraries
Tags digital mathematical libraries, digital mathematics library, EuDML, evaluation, information retrieval, math indexing and retrieval, math information retrieval, MathML, MIaS, query expansion, ranking, similarity search
Tags International impact, Reviewed
Changed by Changed by: RNDr. Pavel Šmerk, Ph.D., učo 3880. Changed: 13/5/2020 19:25.
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.
MUNI/A/1213/2017, internal MU codeName: Aplikovaný výzkum na FI: bezpečnost počítačových systémů, SW architektury kritických infrastruktur, zpracování velkých dat, vizualizace dat a virtuální realita
Investor: Masaryk University, Grant Agency of Masaryk University, Category A
1ET200190513, research and development projectName: DML-CZ: Česká digitální matematická knihovna
Investor: Academy of Sciences of the Czech Republic, Information society (National programme of research)
250503, internal MU codeName: The European Digital Mathematics Library (Acronym: EuDML)
Investor: European Union, Competitiveness and inovation framework programme
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