Legal document retrieval across languages: topic hierarchies based on synsets

التفاصيل البيبلوغرافية
العنوان: Legal document retrieval across languages: topic hierarchies based on synsets
المؤلفون: Badenes-Olmedo, Carlos, Redondo-Garcia, Jose-Luis, Corcho, Oscar
سنة النشر: 2019
المجموعة: Computer Science
مصطلحات موضوعية: Computer Science - Information Retrieval, Computer Science - Digital Libraries
الوصف: Cross-lingual annotations of legislative texts enable us to explore major themes covered in multilingual legal data and are a key facilitator of semantic similarity when searching for similar documents. Multilingual probabilistic topic models have recently emerged as a group of semi-supervised machine learning models that can be used to perform thematic explorations on collections of texts in multiple languages. However, these approaches require theme-aligned training data to create a language-independent space, which limits the amount of scenarios where this technique can be used. In this work, we provide an unsupervised document similarity algorithm based on hierarchies of multi-lingual concepts to describe topics across languages. The algorithm does not require parallel or comparable corpora, or any other type of translation resource. Experiments performed on the English, Spanish, French and Portuguese editions of JCR-Acquis corpora reveal promising results on classifying and sorting documents by similar content.
Comment: IberLegal Workshop co-located with Jurix 2019
نوع الوثيقة: Working Paper
URL الوصول: http://arxiv.org/abs/1911.12637
رقم الانضمام: edsarx.1911.12637
قاعدة البيانات: arXiv