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OPMES: A Similarity Search Engine for Mathematical Content

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Advances in Information Retrieval (ECIR 2016)

Part of the book series: Lecture Notes in Computer Science ((LNISA,volume 9626))

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Abstract

This paper presents details about a new mathematical search engine, i.e., OPMES. This search engine leverages operator trees in both representation and relevance modeling of the mathematical content. More specifically, OPMES represents mathematical expressions using operator trees, and then indexes each expression based on all the leaf-root paths of the generated operator tree. Such data structures enable OPMES to implement an efficient two-stage query processing technique. The system first identifies structurally relevant expressions based on the matching of the leaf-root paths, and then further ranks them based on their symbolic similarity to the query.

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Notes

  1. 1.

    https://mir.fi.muni.cz/mias/.

  2. 2.

    http://saskatoon.cs.rit.edu/tangent/random.

  3. 3.

    http://search.mathweb.org.

References

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Author information

Authors and Affiliations

  1. University of Delaware, Newark, DE, USA

    Wei Zhong & Hui Fang

Authors
  1. Wei Zhong
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  2. Hui Fang
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Corresponding author

Correspondence to Hui Fang .

Editor information

Editors and Affiliations

  1. Department of Information Engineering, University of Padua, Padova, Italy

    Nicola Ferro

  2. Faculty of Informatics, University of Lugano (USI), Lugano, Switzerland

    Fabio Crestani

  3. Department of Computer Science, Katholieke Universiteit Leuven, Heverlee, Belgium

    Marie-Francine Moens

  4. Systèmes d’informations, Big Data et Recherche d’Information, Institut de Recherche en Informatique de Toulouse IRIT/équipe SIG, Toulouse Cedex 04, France

    Josiane Mothe

  5. Yahoo! Labs London, London, UK

    Fabrizio Silvestri

  6. Department of Information Engineering, University of Padua, Padova, Italy

    Giorgio Maria Di Nunzio

  7. TU Delft - EWI/ST/WIS, Delft, The Netherlands

    Claudia Hauff

  8. Department of Information Engineering, University of Padua, Padova, Italy

    Gianmaria Silvello

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© 2016 Springer International Publishing Switzerland

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Cite this paper

Zhong, W., Fang, H. (2016). OPMES: A Similarity Search Engine for Mathematical Content. In: Ferro, N., et al. Advances in Information Retrieval. ECIR 2016. Lecture Notes in Computer Science(), vol 9626. Springer, Cham. https://doi.org/10.1007/978-3-319-30671-1_79

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  • DOI: https://doi.org/10.1007/978-3-319-30671-1_79

  • Publisher Name: Springer, Cham

  • Print ISBN: 978-3-319-30670-4

  • Online ISBN: 978-3-319-30671-1

  • eBook Packages: Computer ScienceComputer Science (R0)

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