Query Generation and Buffer Mechanism: Towards a better conversational agent for legal case retrieval. Issue 5 (September 2022)
- Record Type:
- Journal Article
- Title:
- Query Generation and Buffer Mechanism: Towards a better conversational agent for legal case retrieval. Issue 5 (September 2022)
- Main Title:
- Query Generation and Buffer Mechanism: Towards a better conversational agent for legal case retrieval
- Authors:
- Liu, Bulou
Wu, Yueyue
Zhang, Fan
Liu, Yiqun
Wang, Zhihong
Li, Chenliang
Zhang, Min
Ma, Shaoping - Abstract:
- Abstract: In legal case retrieval, existing work has shown that human-mediated conversational search can improve users' search experience. In practice, a suitable workflow can provide guidelines for constructing a machine-mediated agent replacing of human agents. Therefore, we conduct a comparison analysis and summarize two challenges when directly applying the conversational agent workflow in web search to legal case retrieval: (1) It is complex for agents to express their understanding of users' information need. (2) Selecting a candidate case from the SERPs is more difficult for agents, especially at the early stage of the search process. To tackle these challenges, we propose a suitable conversational agent workflow in legal case retrieval, which contains two additional key modules compared with that in web search: Query Generation and Buffer Mechanism . A controlled user experiment with three control groups, using the whole workflow or removing one of these two modules, is conducted. The results demonstrate that the proposed workflow can actually support conversational agents working more efficiently, and help users save search effort, leading to higher search success and satisfaction for legal case retrieval. We further construct a large-scale dataset and provide guidance on the machine-mediated conversational search system for legal case retrieval. Highlights: Conversational search can improve users' satisfaction in legal case retrieval. A suitable workflow isAbstract: In legal case retrieval, existing work has shown that human-mediated conversational search can improve users' search experience. In practice, a suitable workflow can provide guidelines for constructing a machine-mediated agent replacing of human agents. Therefore, we conduct a comparison analysis and summarize two challenges when directly applying the conversational agent workflow in web search to legal case retrieval: (1) It is complex for agents to express their understanding of users' information need. (2) Selecting a candidate case from the SERPs is more difficult for agents, especially at the early stage of the search process. To tackle these challenges, we propose a suitable conversational agent workflow in legal case retrieval, which contains two additional key modules compared with that in web search: Query Generation and Buffer Mechanism . A controlled user experiment with three control groups, using the whole workflow or removing one of these two modules, is conducted. The results demonstrate that the proposed workflow can actually support conversational agents working more efficiently, and help users save search effort, leading to higher search success and satisfaction for legal case retrieval. We further construct a large-scale dataset and provide guidance on the machine-mediated conversational search system for legal case retrieval. Highlights: Conversational search can improve users' satisfaction in legal case retrieval. A suitable workflow is utilized to enhances agents' performance. A large-scale dataset for constructing conversational legal case retrieval system. … (more)
- Is Part Of:
- Information processing & management. Volume 59:Issue 5(2022)
- Journal:
- Information processing & management
- Issue:
- Volume 59:Issue 5(2022)
- Issue Display:
- Volume 59, Issue 5 (2022)
- Year:
- 2022
- Volume:
- 59
- Issue:
- 5
- Issue Sort Value:
- 2022-0059-0005-0000
- Page Start:
- Page End:
- Publication Date:
- 2022-09
- Subjects:
- Legal case retrieval -- Conversational agent -- Workflow -- User study
Information storage and retrieval systems -- Periodicals
Information science -- Periodicals
Systèmes d'information -- Périodiques
Sciences de l'information -- Périodiques
Information science
Information storage and retrieval systems
Periodicals
658.4038 - Journal URLs:
- http://www.sciencedirect.com/science/journal/03064573 ↗
http://www.elsevier.com/journals ↗ - DOI:
- 10.1016/j.ipm.2022.103051 ↗
- Languages:
- English
- ISSNs:
- 0306-4573
- Deposit Type:
- Legaldeposit
- View Content:
- Available online (eLD content is only available in our Reading Rooms) ↗
- Physical Locations:
- British Library DSC - 4493.893000
British Library DSC - BLDSS-3PM
British Library HMNTS - ELD Digital store - Ingest File:
- 23283.xml