Representation Learning and Similarity of Legal Judgements using Citation Networks Article Swipe
Harshit Jain
,
Naveen Pundir
·
YOU?
·
· 2021
· Open Access
·
· DOI: https://doi.org/10.5121/csit.2021.112302
YOU?
·
· 2021
· Open Access
·
· DOI: https://doi.org/10.5121/csit.2021.112302
India and many other countries like UK, Australia, Canada follow the ‘common law system’ which gives substantial importance to prior related cases in determining the outcome of the current case. Better similarity methods can help in finding earlier similar cases, which can help lawyers searching for precedents. Prior approaches in computing similarity of legal judgements use a basic representation which is either abag-of-words or dense embedding which is learned by only using the words present in the document. They, however, either neglect or do not emphasize the vital ‘legal’ information in the judgements, e.g. citations to prior cases, act and article numbers or names etc. In this paper, we propose a novel approach to learn the embeddings of legal documents using the citationnetwork of documents. Experimental results demonstrate that the learned embedding is at par with the state-of-the-art methods for document similarity on a standard legal dataset.
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- Type
- article
- Language
- en
- Landing Page
- http://doi.org/10.5121/csit.2021.112302
- https://doi.org/10.5121/csit.2021.112302
- OA Status
- hybrid
- References
- 12
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- 10
- OpenAlex ID
- https://openalex.org/W4200126321
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https://openalex.org/W4200126321Canonical identifier for this work in OpenAlex
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https://doi.org/10.5121/csit.2021.112302Digital Object Identifier
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Representation Learning and Similarity of Legal Judgements using Citation NetworksWork title
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articleOpenAlex work type
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enPrimary language
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2021Year of publication
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2021-12-23Full publication date if available
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Harshit Jain, Naveen PundirList of authors in order
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https://doi.org/10.5121/csit.2021.112302Publisher landing page
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https://doi.org/10.5121/csit.2021.112302Direct link to full text PDF
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YesWhether a free full text is available
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hybridOpen access status per OpenAlex
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Similarity (geometry), Representation (politics), Computer science, Embedding, Citation, Neglect, Information retrieval, Artificial intelligence, Natural language processing, Psychology, Political science, Law, Image (mathematics), World Wide Web, Psychiatry, PoliticsTop concepts (fields/topics) attached by OpenAlex
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| sustainable_development_goals[0].id | https://metadata.un.org/sdg/16 |
| sustainable_development_goals[0].score | 0.75 |
| sustainable_development_goals[0].display_name | Peace, Justice and strong institutions |
| citation_normalized_percentile.value | 0.40400668 |
| citation_normalized_percentile.is_in_top_1_percent | False |
| citation_normalized_percentile.is_in_top_10_percent | False |