Expert Finding in Legal Community Question Answering
Expert finding has been well-studied in community question answering (QA) systems in various domains. However, none of these studies addresses expert finding in the legal domain, where the goal is for citizens to find lawyers based on their expertise. In the legal domain, there is a large knowledge gap between the experts and the searchers, and the content on the legal QA websites consist of a combination formal and informal communication. In this paper, we propose methods for generating query-dependent textual profiles for lawyers covering several aspects including sentiment, comments, and recency. We combine query-dependent profiles with existing expert finding methods. Our experiments are conducted on a novel dataset gathered from an online legal QA service. We discovered that taking into account different lawyer profile aspects improves the best baseline model. We make our dataset publicly available for future work.
Code (1)
Tasks
Community Question AnsweringQuestion AnsweringMethods 이 논문이 사용한 방법론
Similar Papers 제목 키워드 기반
Towards Robust Expert Finding in Community Question Answering Platforms
This paper introduces TUEF, a topic-oriented user-interaction model for fair Expert Finding in Community Question Answering (CQA) platforms. The Expert Finding task in CQA platforms involves identifying proficient users …
Community Question AnsweringQuestion AnsweringTowards the Exploitation of LLM-based Chatbot for Providing Legal Support to Palestinian Cooperatives
With the ever-increasing utilization of natural language processing (NLP), we started to witness over the past few years a significant transformation in our interaction with legal texts. This technology has advanced the …
ChatbotQuestion AnsweringExploring the State of the Art in Legal QA Systems
Answering questions related to the legal domain is a complex task, primarily due to the intricate nature and diverse range of legal document systems. Providing an accurate answer to a legal query typically necessitates s…
ArticlesNatural Language UnderstandingQuestion AnsweringLegal Question-Answering in the Indian Context: Efficacy, Challenges, and Potential of Modern AI Models
Legal QA platforms bear the promise to metamorphose the manner in which legal experts engage with jurisprudential documents. In this exposition, we embark on a comparative exploration of contemporary AI frameworks, gaugi…
Natural Language QueriesQuestion AnsweringRetrievalLeveraging Topic Specificity and Social Relationships for Expert Finding in Community Question Answering Platforms
Online Community Question Answering (CQA) platforms have become indispensable tools for users seeking expert solutions to their technical queries. The effectiveness of these platforms relies on their ability to identify …
Community Question AnsweringLearning-To-RankQuestion AnsweringSpecificity