JOURNAL ARTICLE

Non-factoid Question Answering in the Legal Domain

Abstract

Non-factoid question answering in the legal domain must provide legally correct, jurisdictionally relevant, and conversationally responsive answers to user-entered questions. We present work done on a QA system that is entirely based on IR and NLP, and does not rely on a structured knowledge base. Our system retrieves concise one-sentence answers for basic questions about the law. It is not restricted in scope to particular topics or jurisdictions. The corpus of potential answers contains approximately 22M documents classified to over 120K legal topics.

Keywords:
Question answering Computer science Domain (mathematical analysis) Information retrieval Artificial intelligence Natural language processing Mathematics

Metrics

2
Cited By
0.15
FWCI (Field Weighted Citation Impact)
9
Refs
0.56
Citation Normalized Percentile
Is in top 1%
Is in top 10%

Citation History

Topics

Topic Modeling
Physical Sciences →  Computer Science →  Artificial Intelligence
Natural Language Processing Techniques
Physical Sciences →  Computer Science →  Artificial Intelligence
Multi-Agent Systems and Negotiation
Physical Sciences →  Computer Science →  Artificial Intelligence

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