A visual search engine for Bangladeshi laws

November 14, 2017 Β· Declared Dead Β· πŸ› arXiv.org

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Authors Manash Kumar Mandal, Pinku Deb Nath, Arpeeta Shams Mizan, Nazmus Saquib arXiv ID 1711.05233 Category cs.HC: Human-Computer Interaction Cross-listed cs.CY, stat.ML Citations 0 Venue arXiv.org Last Checked 5 months ago
Abstract
Browsing and finding relevant information for Bangladeshi laws is a challenge faced by all law students and researchers in Bangladesh, and by citizens who want to learn about any legal procedure. Some law archives in Bangladesh are digitized, but lack proper tools to organize the data meaningfully. We present a text visualization tool that utilizes machine learning techniques to make the searching of laws quicker and easier. Using Doc2Vec to layout law article nodes, link mining techniques to visualize relevant citation networks, and named entity recognition to quickly find relevant sections in long law articles, our tool provides a faster and better search experience to the users. Qualitative feedback from law researchers, students, and government officials show promise for visually intuitive search tools in the context of governmental, legal, and constitutional data in developing countries, where digitized data does not necessarily pave the way towards an easy access to information.
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