Answer Interaction in Non-factoid Question Answering Systems

被引：16
|
作者：
Qu, Chen [1 ]
Yang, Liu [1 ]
Croft, W. Bruce [1 ]
Scholer, Falk [2 ]
Zhang, Yongfeng [3 ]
机构：
[1] Univ Massachusetts, Amherst, MA 01003 USA
[2] RMIT Univ, Melbourne, Vic, Australia
[3] Rutgers State Univ, New Brunswick, NJ USA
来源：
PROCEEDINGS OF THE 2019 CONFERENCE ON HUMAN INFORMATION INTERACTION AND RETRIEVAL (CHIIR'19) | 2019年
关键词：
User Interaction; Answer Interaction; Answer Presentation; Non-factoid Question Answering; Information-seeking;
D O I：
10.1145/3295750.3298946
中图分类号：
TP [自动化技术、计算机技术];
学科分类号：
0812 ;
摘要：
Information retrieval systems are evolving from document retrieval to answer retrieval. Web search logs provide large amounts of data about how people interact with ranked lists of documents, but very little is known about interaction with answer texts. In this paper, we use Amazon Mechanical Turk to investigate three answer presentation and interaction approaches in a non-factoid question answering setting. We find that people perceive and react to good and bad answers very differently, and can identify good answers relatively quickly. Our results provide the basis for further investigation of effective answer interaction and feedback methods.
引用
收藏
页码：249 / 253
页数：5
相关论文
共 50 条
  • [1] Hybrid Answer Selection Model for Non-Factoid Question Answering
    Ma, Rongqiang
    Zhang, Jian
    Li, Miao
    Chen, Lei
    Gao, Jin
    2017 INTERNATIONAL CONFERENCE ON ASIAN LANGUAGE PROCESSING (IALP), 2017, : 371 - 373
  • [2] A systematic review of question answering systems for non-factoid questions
    Eduardo Gabriel Cortes
    Vinicius Woloszyn
    Dante Barone
    Sebastian Möller
    Renata Vieira
    Journal of Intelligent Information Systems, 2022, 58 : 453 - 480
  • [3] A Non-Factoid Question-Answering Taxonomy
    Bolotova, Valeriia
    Blinov, Vladislav
    Scholer, Falk
    Croft, W. Bruce
    Sanderson, Mark
    PROCEEDINGS OF THE 45TH INTERNATIONAL ACM SIGIR CONFERENCE ON RESEARCH AND DEVELOPMENT IN INFORMATION RETRIEVAL (SIGIR '22), 2022, : 1196 - 1207
  • [4] Performance Prediction for Non-Factoid Question Answering
    Hashemi, Helia
    Zamani, Hamed
    Croft, W. Bruce
    PROCEEDINGS OF THE 2019 ACM SIGIR INTERNATIONAL CONFERENCE ON THEORY OF INFORMATION RETRIEVAL (ICTIR'19), 2019, : 55 - 58
  • [5] A systematic review of question answering systems for non-factoid questions
    Cortes, Eduardo Gabriel
    Woloszyn, Vinicius
    Barone, Dante
    Moeller, Sebastian
    Vieira, Renata
    JOURNAL OF INTELLIGENT INFORMATION SYSTEMS, 2022, 58 (03) : 453 - 480
  • [6] MICRON: Multigranular Interaction for Contextualizing RepresentatiON in Non-factoid Question Answering
    Han, Hojae
    Choi, Seungtaek
    Park, Haeju
    Hwang, Seung-won
    2019 CONFERENCE ON EMPIRICAL METHODS IN NATURAL LANGUAGE PROCESSING AND THE 9TH INTERNATIONAL JOINT CONFERENCE ON NATURAL LANGUAGE PROCESSING (EMNLP-IJCNLP 2019): PROCEEDINGS OF THE CONFERENCE, 2019, : 5890 - 5895
  • [7] Exploring Diversification in Non-factoid Question Answering
    Vikraman, Lakshmi
    Croft, W. Bruce
    O'Connor, Brendan
    PROCEEDINGS OF THE 2018 ACM SIGIR INTERNATIONAL CONFERENCE ON THEORY OF INFORMATION RETRIEVAL (ICTIR'18), 2018, : 223 - 226
  • [8] Quantifying Human-Perceived Answer Utility in Non-factoid Question Answering
    Cambazoglu, B. Barla
    Baranova, Valeriia
    Scholer, Falk
    Sanderson, Mark
    Tavakoli, Leila
    Croft, Bruce
    CHIIR '21: PROCEEDINGS OF THE 2021 CONFERENCE ON HUMAN INFORMATION INTERACTION AND RETRIEVAL, 2021, : 75 - 84
  • [9] Non-factoid Question Answering in the Legal Domain
    McElvain, Gayle
    Sanchez, George
    Teo, Don
    Custis, Tonya
    PROCEEDINGS OF THE 42ND INTERNATIONAL ACM SIGIR CONFERENCE ON RESEARCH AND DEVELOPMENT IN INFORMATION RETRIEVAL (SIGIR '19), 2019, : 1395 - 1396
  • [10] Open-Domain Non-factoid Question Answering
    Khvalchik, Maria
    Kulkarni, Anagha
    TEXT, SPEECH, AND DIALOGUE, TSD 2017, 2017, 10415 : 290 - 298
12345