CSTS: Cuckoo Search Based Model for Text Summarization

Exponential growth of information in the web became infeasible for user to sieve useful information very quickly. So solution to such problem now a day is text summarization. Text summarization is the process of creating condensed version of original text by preserving important information in it. This paper presents for the first time a nature inspired cuckoo search optimization algorithm for optimal selection of sentences as summary sentence of intelligent text summarizer. The key aspects of proposed summarizer focus on content coverage and length while reducing redundant information in the summaries. To solve this optimization problem, this model uses inter-sentence relationship and sentence-to-document relationship by considering widely used similarity measure cosine similarity. The inputs for this model are taken from DUC dataset. Whereas the result is evaluated by ROUGE tool and compared with state-of-the-art approaches, in which our model in multi-document summarization have shown significant result than others.

[1]  Elena Lloret,et al.  Text summarisation in progress: a literature review , 2011, Artificial Intelligence Review.

[2]  Anh Viet Truong,et al.  Distribution network reconfiguration for power loss minimization and voltage profile improvement using cuckoo search algorithm , 2015 .

[3]  S. G. Ponnambalam,et al.  Cuckoo Search Algorithm for Optimization of Sequence in PCB Holes Drilling Process , 2012 .

[4]  N. Jawahar,et al.  Reliability-based total cost of ownership approach for supplier selection using cuckoo-inspired hybrid algorithm , 2014 .

[5]  Samrat L. Sabat,et al.  Optimal chiller loading for energy conservation using a new differential cuckoo search approach , 2014 .

[6]  Abbas Khosravi,et al.  Intelligent cuckoo search optimized traffic signal controllers for multi-intersection network , 2015, Expert Syst. Appl..

[7]  Ramasamy Alagirusamy,et al.  Performance analysis and feasibility study of ant colony optimization, particle swarm optimization and cuckoo search algorithms for inverse heat transfer problems , 2015 .

[8]  Lalit Chandra Saikia,et al.  Comparison of performances of several Cuckoo search algorithm based 2DOF controllers in AGC of multi-area thermal system , 2014 .

[9]  Rasim M. Alguliyev,et al.  GenDocSum + MCLR: Generic document summarization based on maximum coverage and less redundancy , 2012, Expert Syst. Appl..

[10]  Lei Huang,et al.  Modeling Document Summarization as Multi-objective Optimization , 2010, 2010 Third International Symposium on Intelligent Information Technology and Security Informatics.

[11]  Thang Trung Nguyen,et al.  Modified cuckoo search algorithm for short-term hydrothermal scheduling , 2015 .

[12]  Rakesh Chandra Balabantaray,et al.  Comparative Study of DE and PSO over Document Summarization , 2015 .

[13]  Azlan Mohd Zain,et al.  Cuckoo Search Algorithm for Optimization Problems—A Literature Review and its Applications , 2014, Appl. Artif. Intell..

[14]  Enrique Herrera-Viedma,et al.  Clustering of web search results based on the cuckoo search algorithm and Balanced Bayesian Information Criterion , 2014, Inf. Sci..

[15]  Rasim M. Alguliyev,et al.  MCMR: Maximum coverage and minimum redundant text summarization model , 2011, Expert Syst. Appl..

[16]  Ashish Kumar Bhandari,et al.  Cuckoo search algorithm and wind driven optimization based study of satellite image segmentation for multilevel thresholding using Kapur's entropy , 2014, Expert Syst. Appl..

[17]  Ting Liu,et al.  A novel approach to update summarization using evolutionary manifold-ranking and spectral clustering , 2012, Expert Syst. Appl..

[18]  Bestoun S. Ahmed,et al.  Achievement of minimized combinatorial test suite for configuration-aware software functional testing using the Cuckoo Search algorithm , 2015, Inf. Softw. Technol..

[19]  Mhamed Zineddine,et al.  Vulnerabilities and mitigation techniques toning in the cloud: A cost and vulnerabilities coverage optimization approach using Cuckoo search algorithm with Lévy flights , 2015, Comput. Secur..

[20]  Rasim M. Alguliyev,et al.  Sentence selection for generic document summarization using an adaptive differential evolution algorithm , 2011, Swarm Evol. Comput..

[21]  Dilek Z. Hakkani-Tür,et al.  A Hybrid Hierarchical Model for Multi-Document Summarization , 2010, ACL.

[22]  Eduard H. Hovy,et al.  Automatic Evaluation of Summaries Using N-gram Co-occurrence Statistics , 2003, NAACL.

[23]  Dragomir R. Radev,et al.  Centroid-based summarization of multiple documents , 2004, Inf. Process. Manag..

[24]  Dragomir R. Radev,et al.  Introduction to the Special Issue on Summarization , 2002, CL.

[25]  Jade Goldstein-Stewart,et al.  The use of MMR, diversity-based reranking for reordering documents and producing summaries , 1998, SIGIR '98.

[26]  Rasim M. Alguliyev,et al.  CDDS: Constraint-driven document summarization models , 2013, Expert Syst. Appl..

[27]  Xin-She Yang,et al.  Cuckoo Search via Lévy flights , 2009, 2009 World Congress on Nature & Biologically Inspired Computing (NaBIC).

[28]  Jianzhou Wang,et al.  Forecasting solar radiation using an optimized hybrid model by Cuckoo Search algorithm , 2015 .

[29]  Xin-She Yang,et al.  Engineering optimisation by cuckoo search , 2010, Int. J. Math. Model. Numer. Optimisation.

[30]  Jade Goldstein-Stewart,et al.  The Use of MMR, Diversity-Based Reranking for Reordering Documents and Producing Summaries , 1998, SIGIR Forum.