Query-focused multi-document text summarization using fuzzy inference

被引:2
作者
Agarwal, Raksha [1 ]
Chatterjee, Niladri [1 ]
机构
[1] Indian Inst Technol Delhi, Dept Math, Delhi 110016, India
关键词
Query-focused text summarization; mamdani fuzzy inference; text similarity; fuzzy ranking; integer linear programming;
D O I
10.3233/JIFS-219252
中图分类号
TP18 [人工智能理论];
学科分类号
081104 ; 0812 ; 0835 ; 1405 ;
摘要
The present paper proposes a fuzzy inference system for query-focused multi-document text summarization (MTS). The overall scheme is based on Mamdani Inferencing scheme which helps in designing Fuzzy Rule base for inferencing about the decision variable from a set of antecedent variables. The antecedent variables chosen for the task are from linguistic and positional heuristics, and similarity of the documents with the user-defined query. The decision variable is the rank of the sentences as decided by the rules. The final summary is generated by solving an Integer Linear Programming problem. For abstraction coreference resolution is applied on the input sentences in the pre-processing step. Although designed on the basis of a small set of antecedent variables the results are very promising.
引用
收藏
页码:4641 / 4652
页数:12
相关论文
共 40 条
  • [1] Fuzzy evolutionary cellular learning automata model for text summarization
    Abbasi-ghalehtaki, Razieh
    Khotanlou, Hassan
    Esmaeilpour, Mansour
    [J]. SWARM AND EVOLUTIONARY COMPUTATION, 2016, 30 : 11 - 26
  • [2] [Anonymous], 2009, P WORKSH INT LIN PRO
  • [3] [Anonymous], 2015, INT J COMPUT SCI INF
  • [4] Banerjee Satanjeev, 2005, P ACL WORKSH INTR EX, P65
  • [5] The anatomy of a large-scale hypertextual Web search engine
    Brin, S
    Page, L
    [J]. COMPUTER NETWORKS AND ISDN SYSTEMS, 1998, 30 (1-7): : 107 - 117
  • [6] Cer D.M., 2018, P EMNLP, DOI 10.18653/v1/D18-2029.
  • [7] Forgues G., 2014, NIPS MOD MACH LEARN, P2
  • [8] Goldstein J., 2000, NAACLANLP 2000 WORKS
  • [9] Graham Y., 2015, P 2015 C EMPIRICAL M, P128
  • [10] Jafari M, 2016, 2016 22ND INTERNATIONAL CONFERENCE ON AUTOMATION AND COMPUTING (ICAC), P256, DOI 10.1109/IConAC.2016.7604928