Interactive extractive search over biomedical corpora

Hillel Taub-Tabib; Micah Shlain; Shoval Sadde; Dan Lahav; Matan Eyal; Yaara Cohen; Yoav Goldberg

Interactive extractive search over biomedical corpora

Hillel Taub-Tabib, Micah Shlain, Shoval Sadde, Dan Lahav, Matan Eyal, Yaara Cohen, Yoav Goldberg

Department of Computer Science

Research output: Chapter in Book/Report/Conference proceeding › Conference contribution › peer-review

15 Scopus citations

Abstract

We present a system that allows life-science researchers to search a linguistically annotated corpus of scientific texts using patterns over dependency graphs, as well as using patterns over token sequences and a powerful variant of boolean keyword queries. In contrast to previous attempts to dependency-based search, we introduce a light-weight query language that does not require the user to know the details of the underlying linguistic representations, and instead to query the corpus by providing an example sentence coupled with simple markup. Search is performed at an interactive speed due to efficient linguistic graphindexing and retrieval engine. This allows for rapid exploration, development and refinement of user queries. We demonstrate the system using example workflows over two corpora: the PubMed corpus including 14,446,243 PubMed abstracts and the CORD-19 dataset, a collection of over 45,000 research papers focused on COVID-19 research. The system is publicly available at https://allenai. github.io/spike

Original language	English
Title of host publication	BioNLP 2020 - 19th SIGBioMed Workshop on Biomedical Language Processing, Proceedings of the Workshop
Publisher	Association for Computational Linguistics (ACL)
Pages	28-37
Number of pages	10
ISBN (Electronic)	9781952148095
State	Published - 2020
Event	19th SIGBioMed Workshop on Biomedical Language Processing, BioNLP 2020 at the 58th Annual Meeting of the Association for Computational Linguistics, ACL 2020 - Virtual, Online, United States Duration: 9 Jul 2020 → …

Publication series

Name	Proceedings of the Annual Meeting of the Association for Computational Linguistics
ISSN (Print)	0736-587X

Conference

Conference	19th SIGBioMed Workshop on Biomedical Language Processing, BioNLP 2020 at the 58th Annual Meeting of the Association for Computational Linguistics, ACL 2020
Country/Territory	United States
City	Virtual, Online
Period	9/07/20 → …

Bibliographical note

Publisher Copyright:
© Association for Computation Linguistics.

Funding

The work performed at BIU is supported by funding from the Europoean Research Council (ERC) under the Europoean Union's Horizon 2020 research and innovation programme, grant agreement No. 802774 (iEXTRACT). Acknowledgements The work performed at BIU is supported by funding from the Europoean Research Council (ERC) under the Europoean Union’s Horizon 2020 research and innovation programme, grant agreement No. 802774 (iEX-TRACT).

Funders	Funder number
Europoean Union's Horizon 2020 research and innovation programme
Europoean Union’s Horizon 2020 research and innovation programme
Horizon 2020 Framework Programme	802774
European Commission

Cite this

Taub-Tabib, H., Shlain, M., Sadde, S., Lahav, D., Eyal, M., Cohen, Y., & Goldberg, Y. (2020). Interactive extractive search over biomedical corpora. In BioNLP 2020 - 19th SIGBioMed Workshop on Biomedical Language Processing, Proceedings of the Workshop (pp. 28-37). (Proceedings of the Annual Meeting of the Association for Computational Linguistics). Association for Computational Linguistics (ACL).

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abstract = "We present a system that allows life-science researchers to search a linguistically annotated corpus of scientific texts using patterns over dependency graphs, as well as using patterns over token sequences and a powerful variant of boolean keyword queries. In contrast to previous attempts to dependency-based search, we introduce a light-weight query language that does not require the user to know the details of the underlying linguistic representations, and instead to query the corpus by providing an example sentence coupled with simple markup. Search is performed at an interactive speed due to efficient linguistic graphindexing and retrieval engine. This allows for rapid exploration, development and refinement of user queries. We demonstrate the system using example workflows over two corpora: the PubMed corpus including 14,446,243 PubMed abstracts and the CORD-19 dataset, a collection of over 45,000 research papers focused on COVID-19 research. The system is publicly available at https://allenai. github.io/spike",

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Taub-Tabib, H, Shlain, M, Sadde, S, Lahav, D, Eyal, M, Cohen, Y & Goldberg, Y 2020, Interactive extractive search over biomedical corpora. in BioNLP 2020 - 19th SIGBioMed Workshop on Biomedical Language Processing, Proceedings of the Workshop. Proceedings of the Annual Meeting of the Association for Computational Linguistics, Association for Computational Linguistics (ACL), pp. 28-37, 19th SIGBioMed Workshop on Biomedical Language Processing, BioNLP 2020 at the 58th Annual Meeting of the Association for Computational Linguistics, ACL 2020, Virtual, Online, United States, 9/07/20.

Interactive extractive search over biomedical corpora. / Taub-Tabib, Hillel; Shlain, Micah; Sadde, Shoval et al.
BioNLP 2020 - 19th SIGBioMed Workshop on Biomedical Language Processing, Proceedings of the Workshop. Association for Computational Linguistics (ACL), 2020. p. 28-37 (Proceedings of the Annual Meeting of the Association for Computational Linguistics).

Research output: Chapter in Book/Report/Conference proceeding › Conference contribution › peer-review

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Taub-Tabib H, Shlain M, Sadde S, Lahav D, Eyal M, Cohen Y et al. Interactive extractive search over biomedical corpora. In BioNLP 2020 - 19th SIGBioMed Workshop on Biomedical Language Processing, Proceedings of the Workshop. Association for Computational Linguistics (ACL). 2020. p. 28-37. (Proceedings of the Annual Meeting of the Association for Computational Linguistics).

Interactive extractive search over biomedical corpora

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Bibliographical note

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