Abstract
A novel approach is proposed for the purpose of market analysis by optimizing the reviews of customers using differential evolutionary algorithm. The approach is further compared with the genetic algorithm for improved results analysis. The customer reviews are analyzed in terms of their hidden sentiments and these sentiments form the basis for the recommendation of a product in comparison to the other product reviews. The differential evolutionary and the genetic algorithms provide an advantage of optimized Sentiwords analysis and further enabling a more efficient product recommendation in terms of the reviews of that product, plus more.
Positive and negative words available at http://www.unc.edu/~ncaren/haphazard/.
Database available at http://snap.stanford.edu/data/web-Amazon.html.
Web data: Product_and_Accessories reviews size:20Â M. Last accessed on 20/02/15.
This is a preview of subscription content, log in via an institution to check access.
Access this chapter
Tax calculation will be finalised at checkout
Purchases are for personal use only
References
Chen, H., Chiang, R., Storey, V.: Busines intelligence and analytics: from big data to big impact. MIS Q. 36(4), 1165–1188 (2012)
Predictive Analytics: Bringing The Tools To The Data, An Oracle White Paper, Sept 2010
Maheshwari, R., Gupta, A., Chandra, N.: Secure authentication using biometric templates in Kerberos. In: 2nd International Conference on Sustainable Global Development (INDIAcom), IEEE, 2015
Aggarwal, C.C., Procopiuc, C., Yu, P.S.: Finding localized associations in market basket data. IEEE Trans. Knowl. Data Eng. 14(1) (2002)
Ravi, V., Kurniawan, H., Thai, P.N.K., Kumar, P.R.: Soft computing system for bank performance prediction. Appl. Soft Comput. Elsevier (2007)
Kiran, N.R., Ravi, V.: Software reliability prediction by soft computing techniques. Elsevier (2007)
Maqsood, I., Khan, M.R., Abraham, A.: An ensemble of neural networks for weather forecasting. Neural Comput. Appl. (2004)
Pratap, A., Kanimozhiselvi, C.S., Vijayakumar, R., Pramod, K.V.: Soft computing models for the predictive grading of childhood autism—a comparitive study. Int. J. Soft Comput. Eng. (IJSCE) 4(3) (2014)
Acampora, G., Cosma, G.: A hybrid computational intelligence approach for efficiently evaluating customer sentiments in E-commerce reviews. In: IEEE Symposium on Intelligent Agents, 2014
Baiza-Yates, R., Ribeiro-Neto, B.: Modern Information Retrieval. ACM Press/Addison-Wesley (1999)
Porter, M.F.: An algorithm for suffix stipping. Program: Electron. Libr. Inf. Syst. 14(3), 130–137 (1980)
Suresh, K., Ghosh, S., Kundu, D., Das, S.: Clustering with mulitobjective differential evolution—a comparative study. In: The International Conference on Advanced Computing Technologies (ICACT 2008), Hyderabad, 2008
Daoudi, M., Hamena, S., Benmounah, Z., Batouche, M.: Parallel differential evolution clustering algorithm based on MapReduce. In: International Conference on Soft Computing and Pattern Recognition, IEEE, 2014
Abbass, H.A., Sarker, R.: The pareto differential evolution algorithm. Int. J. Artif. Intell. Tools 11(4), 531–552 (2002)
Karwa, S., Chatterjee, N.L: Discrete differential evolution for text summarization. In: International Conference on Information Technology, IEEE, 2014
McAuley, J., Leskovec, J.: Hidden factors and hidden topics: understanding rating dimensions with the review text. In: The Proceedings of the 7th ACM Conference on Recommender Systems, ser RecSys ’13. New York, NY, USA: ACM, 2013, pp. 165–172. http://doi.acm.org/10.1145/2507157.2507163.
Gupta, A.: Big data analysis using computational intelligence and Hadoop: a study. In: 2nd International Conference on Computing for Sustainable Global Development (INDIAcom), IEEE, 2015
Author information
Authors and Affiliations
Corresponding author
Editor information
Editors and Affiliations
Rights and permissions
Copyright information
© 2016 Springer Science+Business Media Singapore
About this paper
Cite this paper
Apoorva Gupta, Manoj Kumar, Sushil Kumar (2016). A Novel Approach for Market Prediction Using Differential Evolution and Genetic Algorithm. In: Pant, M., Deep, K., Bansal, J., Nagar, A., Das, K. (eds) Proceedings of Fifth International Conference on Soft Computing for Problem Solving. Advances in Intelligent Systems and Computing, vol 436. Springer, Singapore. https://doi.org/10.1007/978-981-10-0448-3_31
Download citation
DOI: https://doi.org/10.1007/978-981-10-0448-3_31
Published:
Publisher Name: Springer, Singapore
Print ISBN: 978-981-10-0447-6
Online ISBN: 978-981-10-0448-3
eBook Packages: EngineeringEngineering (R0)