Performance analysis of Modified Shuffled Frog leaping Algorithm for Multi-document Summarization Problem

Due to massive growth of Web information, handling useful information has become a challenging issue in now-a-days.  In the past few decades, text summarization is considered as one of the solution to obtained relevant information from extensive collection of information. In this paper, a novel approach using modified shuffled frog leaping algorithm (MSFLA) to extract the important sentence from multiple documents is presented. The effectiveness of MSFLA algorithm for summarization model is evaluated by comparing the ROUGE score and statistical analysis of the model with respect to results of other summarization models. The models are demonstrated by the simulation results over DUC datasets. In the present work, it elucidates that MSFLA based model improves the results and find advisable solution for summary extraction

[1]  Tarun Kumar Sharma,et al.  Opposition based learning ingrained shuffled frog-leaping algorithm , 2017, J. Comput. Sci..

[2]  Regina Barzilay,et al.  Towards Multidocument Summarization by Reformulation: Progress and Prospects , 1999, AAAI/IAAI.

[3]  P. V. G. D. Prasad Reddy,et al.  A Modified and Efficient Shuffled Frog Leaping Algorithm (MSFLA) for Unsupervised Data Clustering , 2011, ACC.

[4]  Homa Amirian,et al.  Solving a grey project selection scheduling using a simulated shuffled frog leaping algorithm , 2017, Comput. Ind. Eng..

[5]  Ju Jiang,et al.  Modified shuffled frog leaping algorithm optimized control for air-breathing hypersonic flight vehicle , 2016 .

[6]  Tarun Kumar Sharma,et al.  Centroid Mutation Embedded Shuffled Frog-Leaping Algorithm , 2015 .

[7]  Daobo Wang,et al.  Modified shuffled frog leaping algorithm for optimization of UAV flight controller , 2011, Int. J. Intell. Comput. Cybern..

[8]  P. J. Pawar,et al.  Optimal sequence of hole-making operations using particle swarm optimization and modified shuffled frog leaping algorithm , 2016 .

[9]  Thai-Hoang Huynh,et al.  A modified shuffled frog leaping algorithm for optimal tuning of multivariable PID controllers , 2008, 2008 IEEE International Conference on Industrial Technology.

[10]  Sarada Prasad Sarmah,et al.  Shuffled frog leaping algorithm and its application to 0/1 knapsack problem , 2014, Appl. Soft Comput..

[11]  Zhen Liu,et al.  A lévy flight-based shuffled frog-leaping algorithm and its applications for continuous optimization problems , 2016, Appl. Soft Comput..

[12]  Rakesh Chandra Balabantaray,et al.  An evolutionary framework for multi document summarization using Cuckoo search approach: MDSCSA , 2018 .

[13]  Hans Peter Luhn,et al.  The Automatic Creation of Literature Abstracts , 1958, IBM J. Res. Dev..

[14]  Rajashree Dash.  An improved shuffled frog leaping algorithm based evolutionary framework for currency exchange rate prediction , 2017 .

[15]  Parmeet Kaur,et al.  Resource provisioning and work flow scheduling in clouds using augmented Shuffled Frog Leaping Algorithm , 2017, J. Parallel Distributed Comput..

[16]  Hany M. Hasanien,et al.  Shuffled Frog Leaping Algorithm for Photovoltaic Model Identification , 2015, IEEE Transactions on Sustainable Energy.

[17]  Regina Barzilay,et al.  Information Fusion in the Context of Multi-Document Summarization , 1999, ACL.

[18]  Yanfeng Wang,et al.  An improved shuffled frog leaping algorithm with cognitive behavior , 2008, 2008 7th World Congress on Intelligent Control and Automation.

[19]  Rakesh Chandra Balabantaray,et al.  Cat swarm optimization based evolutionary framework for multi document summarization , 2017 .

[20]  C. Borror.  Nonparametric Statistical Methods, 2nd, Ed. , 2001 .

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

[22]  Ondrej Krejcar,et al.  Modified frequency-based term weighting schemes for text classification , 2017, Appl. Soft Comput..