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Towards a KOS to Manage and Retrieve Legal Data

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Information Systems and Technologies (WorldCIST 2023)

Part of the book series: Lecture Notes in Networks and Systems ((LNNS,volume 800))

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Abstract

Legislation is a technical domain characterized by highly specialized knowledge forming a large corpus where content is interdependent in nature, but the context is poorly formalized. Typically, the legal domain involves several document types that can be related. Amendments, past judicial interpretations, or new laws can refer to other legal documents to contextualize or support legal formulation. Lengthy and complex texts are frequently unstructured or in some cases semi-structured. Therefore, several problems arise since legal documents, articles, or specific constraints can be cited and referenced differently. Based on legal annotations from a real-world scenario, an architectural approach for modeling a Knowledge Organization System for classifying legal documents and the related legal objects is presented. Data is summarized and classified using a topic modeling approach, with a view toward the improvement of browsing and retrieval of main legal topics and associated terms.

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Notes

  1. 1.

    https://dre.pt/dre/home.

  2. 2.

    http://www.dgsi.pt.

  3. 3.

    https://informador.pt/legislacao/lexit/.

  4. 4.

    https://wordpress.org.

  5. 5.

    https://eur-lex.europa.eu/eli-register/about.html.

  6. 6.

    https://spacy.io.

  7. 7.

    Natural Language Processing.

References

  1. Angelov, D.: Top2Vec: distributed representations of topics. Comput. Lang. (2020)

    Google Scholar 

  2. Casanovas, P., Palmirani, M., Peroni, S., Engers, T.V., Vitali, F.: Semantic web for the legal domain: the next step. Semantic Web 7, 213–227 (3 2016)

    Google Scholar 

  3. Ceci, M., Gangemi, A.: An owl ontology library representing judicial interpretations. Semantic Web 7, 229–253 (2016)

    Article  Google Scholar 

  4. Devins, C., Felin, T., Kauffman, S., Koppl, R.: The law and big data. Cornell J. Law Public Policy 27(2), 357–413 (2017)

    Google Scholar 

  5. Fawei, B., Pan, J.Z., Kollingbaum, M., Wyner, A.Z.: A semi-automated ontology construction for legal question answering. N. Gener. Comput. 37, 453–478 (2019)

    Article  Google Scholar 

  6. Gangemi, A., Presutti, V.: Ontology design patterns. In: Staab, S., Studer, R. (eds.) Handbook on Ontologies. IHIS, pp. 221–243. Springer, Heidelberg (2009). https://doi.org/10.1007/978-3-540-92673-3_10

    Chapter  Google Scholar 

  7. Giri, R., Porwal, Y., Shukla, V., Chadha, P., Kaushal, R.: Approaches for information retrieval in legal documents. In: 2017 10th International Conference on Contemporary Computing, IC3 2017, Jan 2018, pp. 1–6 (2018)

    Google Scholar 

  8. Gostojić, S., Milosavljević, B., Konjović, Z.: Ontological model of legal norms for creating and using legislation. Comput. Sci. Inf. Syst. 10, 151–171 (2013)

    Article  Google Scholar 

  9. Grüninger, M., Fox, M.S.: The role of competency questions in enterprise engineering. In: Rolstadås, A. (ed.) Benchmarking — Theory and Practice. IAICT, pp. 22–31. Springer, Boston, MA (1995). https://doi.org/10.1007/978-0-387-34847-6_3

    Chapter  Google Scholar 

  10. Isaac, A., Summers, E.: SKOS Simple Knowledge Organization System Primer, https://www.w3.org/TR/skos-primer/

  11. Joshi, K.P., Gupta, A., Mittal, S., Pearce, C., Joshi, A., Finin, T.: ALDA: cognitive assistant for legal document analytics. In: AAAI Fall Symposium - Technical Report , vol. FS-16-01, pp. 149–152 (2016)

    Google Scholar 

  12. Koniaris, M., Anagnostopoulos, I., Vassiliou, Y.: Evaluation of diversification techniques for legal information retrieval. Algorithms 10, 1–24 (2017)

    Article  MathSciNet  Google Scholar 

  13. Li, G., Wang, Z., Ma, Y.: Combining domain knowledge extraction with graph long short-term memory for learning classification of Chinese legal documents. IEEE Access 7, 139316–139627 (2019)

    Google Scholar 

  14. McCallum, A., Nigam, K., Rennie, J., Seymore, K.: Building domain-specific search engines with machine learning techniques. In: Proceedings of AAAI 1999 Spring Symposium on Intelligent Agents in Cyberspace (1999)

    Google Scholar 

  15. Mihalcea, R., Tarau, P.: TextRank: bringing order into texts. In: Proceedings of EMNLP, vol. 2004, pp. 404–411. Association for Computational Linguistics (2004)

    Google Scholar 

  16. Sapkota, K., Aldea, A., Younas, M., Duce, D.A., Banares-Alcantara, R.: Automating the semantic mapping between regulatory guidelines and organizational processes. SOCA 10, 365–389 (12 2016)

    Google Scholar 

  17. Thomas, A., Sangeetha, S.: A legal case ontology for extracting domain-specific entity-relationships from e-judgments (2017)

    Google Scholar 

  18. Winkels, R., Boer, A., Maat, E.D., Engers, T.V., Breebaart, M., Melger, H.: Constructing a semantic network for legal content. In: Belgian/Netherlands Artificial Intelligence Conference, pp. 405–406 (2005)

    Google Scholar 

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Acknowledgement

This work was supported by the Northern Regional Operational Program, Por- tugal 2020 and European Union, through European Regional Development Fund (ERDF) in the scope of project number 047223 - 17/SI/2019.

Author information

Authors and Affiliations

  1. CIICESI/ESTG, Polytechnic of Porto, rua do Curral, Casa do Curral, 4610-156, Felgueiras, Portugal

    Bruno Oliveira & Cristóvão Sousa

  2. INESC TEC, Rua Dr. Roberto Frias, 4200-465, Porto, Portugal

    Cristóvão Sousa

Authors
  1. Bruno Oliveira
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  2. Cristóvão Sousa
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Corresponding author

Correspondence to Bruno Oliveira .

Editor information

Editors and Affiliations

  1. ISEG, Universidade de Lisboa, Lisbon, Cávado, Portugal

    Alvaro Rocha

  2. College of Engineering, The Ohio State University, Columbus, OH, USA

    Hojjat Adeli

  3. Institute of Data Science and Digital Technologies, Vilnius University, Vilnius, Lithuania

    Gintautas Dzemyda

  4. DCT, Universidade Portucalense, Porto, Portugal

    Fernando Moreira

  5. TeCIP Institute, Scuola Superiore Sant’Anna, Pisa, Italy

    Valentina Colla

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Oliveira, B., Sousa, C. (2024). Towards a KOS to Manage and Retrieve Legal Data. In: Rocha, A., Adeli, H., Dzemyda, G., Moreira, F., Colla, V. (eds) Information Systems and Technologies. WorldCIST 2023. Lecture Notes in Networks and Systems, vol 800. Springer, Cham. https://doi.org/10.1007/978-3-031-45645-9_7

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