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Searching Case Law Judgments by Using Other Judgments as a Query
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A4 Artikkeli konferenssijulkaisussa
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en
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13
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Artificial Intelligence and Natural Language - 9th Conference, AINL 2020, Proceedings, pp. 145-157, Communications in Computer and Information Science ; Volume 1292
Abstract
This paper presents an effective method for case law retrieval based on semantic document similarity and a web application for querying Finnish case law. The novelty of the work comes from the idea of using legal documents for automatic formulation of the query, including case law judgments, legal case descriptions, or other texts. The query documents may be in various formats, including image files with text content. This approach allows efficient search for similar documents without the need to specify a query string or keywords, which can be difficult in this use case. The application leverages two traditional word frequency based methods, TF-IDF and LDA, alongside two modern neural network methods, Doc2Vec and Doc2VecC. Effectiveness of the approach for document relevance ranking has been evaluated using a gold standard set of inter-document similarities. We show that a linear combination of similarities derived from the individual models provides a robust automatic similarity assessment for ranking the case law documents for retrieval.
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Sarsa, S & Hyvönen, E 2020, Searching Case Law Judgments by Using Other Judgments as a Query. in A Filchenkov, J Kauttonen & L Pivovarova (eds), Artificial Intelligence and Natural Language - 9th Conference, AINL 2020, Proceedings. Communications in Computer and Information Science, vol. 1292, Springer, pp. 145-157, Artificial Intelligence and Natural Language, Virtual, Online, 07/10/2020. https://doi.org/10.1007/978-3-030-59082-6_11