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QuantPlorer: Exploration of Quantities in Text

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Advances in Information Retrieval (ECIR 2024)

Part of the book series: Lecture Notes in Computer Science ((LNCS,volume 14612))

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Abstract

Quantities play an important role in documents of various domains such as finance, business, and medicine. Despite the role of quantities, only a limited number of works focus on their extraction from text and even less on creating respective user-friendly document exploration frameworks. In this work, we introduce QuantPlorer, an online quantity extractor and explorer. Through an intuitive web interface, QuantExplorer extracts quantities from unstructured text, enables users to interactively investigate and visualize quantities in text, and it supports filtering based on diverse features, i.e., value ranges, units, trends, and concepts. Furthermore, users can explore and visualize distributions of values for specific units and concepts. Our demonstration is available at https://quantplorer.ifi.uni-heidelberg.de/.

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Notes

  1. 1.

    https://github.com/nielstron/quantulum3 DLA: 12.09.2023.

  2. 2.

    https://github.com/vivkaz/CQE DLA: 12.09.2023.

  3. 3.

    https://flask.palletsprojects.com/ DLA: 28.08.2023.

  4. 4.

    https://spacy.io/ DLA: 28.08.2023.

  5. 5.

    http://getbootstrap.com DLA: 28.08.2023.

  6. 6.

    https://www.chartjs.org/ DLA: 28.08.2023.

References

  1. Almasian, S., Bruseva, M., Gertz, M.: QFinder: a framework for quantity-centric ranking. In: SIGIR 2022: The 45th International ACM SIGIR Conference on Research and Development in Information Retrieval, Madrid, Spain, 11–15 July 2022, pp. 3272–3277. ACM (2022)

    Google Scholar 

  2. Almasian, S., Kazakova, V., Göldner, P., Gertz, M.: CQE: a comprehensive quantity extractor. In: Proceedings of the 2023 Conference on Empirical Methods in Natural Language Processing, EMNLP 2023, Singapore, 6–10 December 2023, pp. 12845–12859. Association for Computational Linguistics (2023)

    Google Scholar 

  3. Devlin, J., Chang, M., Lee, K., Toutanova, K.: BERT: pre-training of deep bidirectional transformers for language understanding. In: Proceedings of the 2019 Conference of the North American Chapter of the Association for Computational Linguistics: Human Language Technologies, NAACL-HLT 2019, Minneapolis, MN, USA, 2–7 June 2019, vol. 1 (Long and Short Papers), pp. 4171–4186. Association for Computational Linguistics (2019)

    Google Scholar 

  4. Foppiano, L., Romary, L., Ishii, M., Tanifuji, M.: Automatic identification and normalisation of physical measurements in scientific literature. In: Proceedings of the ACM Symposium on Document Engineering 2019, Berlin, Germany, 23–26 September 2019, pp. 24:1–24:4. ACM (2019)

    Google Scholar 

  5. Ho, V.T., Ibrahim, Y., Pal, K., Berberich, K., Weikum, G.: Qsearch: answering quantity queries from text. In: Ghidini, C., et al. The Semantic Web - ISWC - 18th International Semantic Web Conference, Proceedings, Part I. Lecture Notes in Computer Science, vol. 11778, pp. 237–257. Springer, Heidelberg (2019). https://doi.org/10.1007/978-3-030-30793-6_14

  6. Ho, V.T., Pal, K., Kleer, N., Berberich, K., Weikum, G.: Entities with quantities: extraction, search, and ranking. In: WSDM 2020: The Thirteenth ACM International Conference on Web Search and Data Mining, Houston, TX, USA, 3–7 February 2020, pp. 833–836. ACM (2020)

    Google Scholar 

  7. Ho, V.T., Pal, K., Razniewski, S., Berberich, K., Weikum, G.: Extracting contextualized quantity facts from web tables. In: WWW 2021: The Web Conference 2021, Virtual Event/Ljubljana, Slovenia, 19–23 April 2021, pp. 4033–4042. ACM/IW3C2 (2021)

    Google Scholar 

  8. Ho, V.T., Pal, K., Weikum, G.: QuTE: answering quantity queries from web tables. In: SIGMOD 2021: International Conference on Management of Data, Virtual Event, China, 20–25 June 2021, pp. 2740–2744. ACM (2021)

    Google Scholar 

  9. Huang, W., Lin, Z., McConnell, C., Karlsson, B.F.: Recognizers-Text: recognition and resolution of numbers, units, and date/time entities expressed across multiple languages (2017)

    Google Scholar 

  10. Li, T., Fang, L., Lou, J., Li, Z., Zhang, D.: AnaSearch: extract, retrieve and visualize structured results from unstructured text for analytical queries. In: WSDM 2021, The Fourteenth ACM International Conference on Web Search and Data Mining, Virtual Event, Israel, 8–12 March 2021, pp. 906–909. ACM (2021)

    Google Scholar 

  11. Roy, S., Vieira, T., Roth, D.: Reasoning about quantities in natural language. Trans. Assoc. Comput. Linguistics 3, 1–13 (2015)

    Article  Google Scholar 

  12. Rybinski, M., et al.: SciHarvester: searching scientific documents for numerical values. In: Proceedings of the 46th International ACM SIGIR Conference on Research and Development in Information Retrieval, SIGIR 2023, Taipei, Taiwan, 23–27 July 2023, pp. 3135–3139. ACM (2023)

    Google Scholar 

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Author information

Authors and Affiliations

  1. Heidelberg University, Heidelberg, Germany

    Satya Almasian, Alexander Kosnac & Michael Gertz

Authors
  1. Satya Almasian
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  2. Alexander Kosnac
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  3. Michael Gertz
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Corresponding author

Correspondence to Satya Almasian .

Editor information

Editors and Affiliations

  1. Georgetown University, Washington, WA, USA

    Nazli Goharian

  2. University of Pisa, PISA, Pisa, Italy

    Nicola Tonellotto

  3. King's College London, London, UK

    Yulan He

  4. University College London, London, UK

    Aldo Lipani

  5. University of Glasgow, Glasgow, UK

    Graham McDonald

  6. University of Glasgow, Glasgow, UK

    Craig Macdonald

  7. University of Glasgow, Glasgow, UK

    Iadh Ounis

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© 2024 The Author(s), under exclusive license to Springer Nature Switzerland AG

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Almasian, S., Kosnac, A., Gertz, M. (2024). QuantPlorer: Exploration of Quantities in Text. In: Goharian, N., et al. Advances in Information Retrieval. ECIR 2024. Lecture Notes in Computer Science, vol 14612. Springer, Cham. https://doi.org/10.1007/978-3-031-56069-9_13

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  • DOI: https://doi.org/10.1007/978-3-031-56069-9_13

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  • Publisher Name: Springer, Cham

  • Print ISBN: 978-3-031-56068-2

  • Online ISBN: 978-3-031-56069-9

  • eBook Packages: Computer ScienceComputer Science (R0)

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