Using Semantic Constraints for Question Answering

被引:1
作者
Zeng, Qingpeng [1 ]
Wu, Shuixiu [2 ]
机构
[1] NanChang Univ, Sch Informat Engn, Nanchang, Peoples R China
[2] Jiangxi Normal Univ, Sch Comp & Informat Engn, Nanchang, Jiangxi, Peoples R China
来源
ENGINEERING SOLUTIONS FOR MANUFACTURING PROCESSES, PTS 1-3 | 2013年 / 655-657卷
关键词
Question Answering; Natural Language Processing; Semantic Constraints;
D O I
10.4028/www.scientific.net/AMR.655-657.1750
中图分类号
TH [机械、仪表工业];
学科分类号
0802 ;
摘要
In this paper, we discuss a technique based on semantic constraints to improve the performance and portability of a reformulation-based question answering system. First, we present a method for acquiring semantic-based reformulations automatically. The goal is to generate patterns from correlative articles based on lexical, syntactic and semantic constraints, and a method to evaluate and re-rank candidate answers that satisfy these constraints is adopted. The evaluation on questions from TREC QA tracks 2003 and 2004 shows that the automatically acquired semantic patterns allows us to avoid the manual work of formulating semantically equivalent reformulations, while still reach an acceptable performance.
引用
收藏
页码:1750 / +
页数:3
相关论文
共 50 条
  • [31] Semantic patterns for user-interactive question answering
    Hao, Tianyong
    Hu, Dawei
    Liu, Wenyin
    Zeng, Qingtian
    CONCURRENCY AND COMPUTATION-PRACTICE & EXPERIENCE, 2008, 20 (07) : 783 - 799
  • [32] Answering engineers' questions using semantic annotations
    Kim, Sanghee
    Bracewell, Rob H.
    Wallace, Ken M.
    AI EDAM-ARTIFICIAL INTELLIGENCE FOR ENGINEERING DESIGN ANALYSIS AND MANUFACTURING, 2007, 21 (02): : 155 - 171
  • [33] Question answering based on pervasive agent ontology and Semantic Web
    Guo, Qinglin
    Zhang, Ming
    KNOWLEDGE-BASED SYSTEMS, 2009, 22 (06) : 443 - 448
  • [34] Semantic passage segmentation based on sentence topics for question answering
    Oh, Hyo-Jung
    Myaeng, Sung Hyon
    Jang, Myung-Gil
    INFORMATION SCIENCES, 2007, 177 (18) : 3696 - 3717
  • [35] gMatch: Knowledge base question answering via semantic matching
    Jiao, Jie
    Wang, Shujun
    Zhang, Xiaowang
    Wang, Longbiao
    Feng, Zhiyong
    Wang, Junhu
    KNOWLEDGE-BASED SYSTEMS, 2021, 228
  • [36] Indexing UMLS Semantic Types for Medical Question-Answering
    Delbecque, Thierry
    Jacquemart, Pierre
    Zweigenbaum, Pierre
    CONNECTING MEDICAL INFORMATICS AND BIO-INFORMATICS, 2005, 116 : 805 - 810
  • [37] Semantic-Syntactic Analysis for Question Answering and Definition Extraction
    Shelmanov A.O.
    Kamenskaya M.A.
    Ananyeva M.I.
    Smirnov I.V.
    Scientific and Technical Information Processing, 2017, 44 (6) : 412 - 423
  • [38] Semantic Models for Answer Re-ranking in Question Answering
    Molino, Piero
    SIGIR'13: THE PROCEEDINGS OF THE 36TH INTERNATIONAL ACM SIGIR CONFERENCE ON RESEARCH & DEVELOPMENT IN INFORMATION RETRIEVAL, 2013, : 1146 - 1146
  • [39] IQA: Interactive query construction in semantic question answering systems
    Zafar, Hamid
    Dubey, Mohnish
    Lehmann, Jens
    Demidova, Elena
    JOURNAL OF WEB SEMANTICS, 2020, 64 (64):
  • [40] Question answering for Biology
    Neves, Mariana
    Leser, Ulf
    METHODS, 2015, 74 : 36 - 46