Accelerating Substructure Similarity Search for Formula Retrieval

Formula retrieval systems using substructure matching are effective, but suffer from slow retrieval times caused by the complexity of structure matching. We present a specialized inverted index and rank-safe dynamic pruning algorithm for faster substructure retrieval. Formulas are indexed from their...

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Detalles Bibliográficos
Autores principales: Zhong, Wei, Rohatgi, Shaurya, Wu, Jian, Giles, C. Lee, Zanibbi, Richard
Formato: Online Artículo Texto
Lenguaje:English
Publicado: 2020
Materias:
Article
Acceso en línea:https://www.ncbi.nlm.nih.gov/pmc/articles/PMC7148252/
http://dx.doi.org/10.1007/978-3-030-45439-5_47
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author Zhong, Wei
Rohatgi, Shaurya
Wu, Jian
Giles, C. Lee
Zanibbi, Richard
author_facet Zhong, Wei
Rohatgi, Shaurya
Wu, Jian
Giles, C. Lee
Zanibbi, Richard
author_sort Zhong, Wei
collection PubMed
description Formula retrieval systems using substructure matching are effective, but suffer from slow retrieval times caused by the complexity of structure matching. We present a specialized inverted index and rank-safe dynamic pruning algorithm for faster substructure retrieval. Formulas are indexed from their Operator Tree (OPT) representations. Our model is evaluated using the NTCIR-12 Wikipedia Formula Browsing Task and a new formula corpus produced from Math StackExchange posts. Our approach preserves the effectiveness of structure matching while allowing queries to be executed in real-time.
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spelling pubmed-71482522020-04-13 Accelerating Substructure Similarity Search for Formula Retrieval Zhong, Wei Rohatgi, Shaurya Wu, Jian Giles, C. Lee Zanibbi, Richard Advances in Information Retrieval Article Formula retrieval systems using substructure matching are effective, but suffer from slow retrieval times caused by the complexity of structure matching. We present a specialized inverted index and rank-safe dynamic pruning algorithm for faster substructure retrieval. Formulas are indexed from their Operator Tree (OPT) representations. Our model is evaluated using the NTCIR-12 Wikipedia Formula Browsing Task and a new formula corpus produced from Math StackExchange posts. Our approach preserves the effectiveness of structure matching while allowing queries to be executed in real-time. 2020-03-17 /pmc/articles/PMC7148252/ http://dx.doi.org/10.1007/978-3-030-45439-5_47 Text en © Springer Nature Switzerland AG 2020 This article is made available via the PMC Open Access Subset for unrestricted research re-use and secondary analysis in any form or by any means with acknowledgement of the original source. These permissions are granted for the duration of the World Health Organization (WHO) declaration of COVID-19 as a global pandemic.
spellingShingle Article
Zhong, Wei
Rohatgi, Shaurya
Wu, Jian
Giles, C. Lee
Zanibbi, Richard
Accelerating Substructure Similarity Search for Formula Retrieval
title Accelerating Substructure Similarity Search for Formula Retrieval
title_full Accelerating Substructure Similarity Search for Formula Retrieval
title_fullStr Accelerating Substructure Similarity Search for Formula Retrieval
title_full_unstemmed Accelerating Substructure Similarity Search for Formula Retrieval
title_short Accelerating Substructure Similarity Search for Formula Retrieval
title_sort accelerating substructure similarity search for formula retrieval
topic Article
url https://www.ncbi.nlm.nih.gov/pmc/articles/PMC7148252/
http://dx.doi.org/10.1007/978-3-030-45439-5_47
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AT gilesclee acceleratingsubstructuresimilaritysearchforformularetrieval
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