Cluster Computing

, Volume 22, Supplement 3, pp 6977–6984 | Cite as

Analyzing cloud based reviews for product ranking using feature based clustering algorithm

  • N. GobiEmail author
  • A. Rathinavelu


The rapid expansion of e-commerce improves customer experience and online businesses largely. Customers buy products based on reviews provided by the users of the product through cloud. Opinion of customers plays a huge role in decision making for business. Opinion mining helps in comparison of products by identifying the main features commented upon by customers and also ranking the products. Most of the opinion mining systems identify only the explicitly mentioned features from the reviews. Identification of implicit features and considering the context of the reviewer about a product plays a huge role in better decision making. The proposed system uses a novel approach for identifying explicit features, implicit features and the context of the reviewer through soft clustering techniques for forming the clusters. Since opinion comparison and ranking of products are based on multi-alternative criteria, a multi criteria decision making approach is used for ranking the products. An experiment is designed to test the proposed method using the reviews collected from Amazon cloud set for mobile phone and camera reviews. The result shows that the proposed method identifies the key features of the products and provides the better ranking of products as it considers the explicit features, implicit features and the context of the reviewer.


Sentiment analysis Feature extraction Product ranking Soft cluster Multi criteria decision making Fuzzy approach 


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© Springer Science+Business Media, LLC, part of Springer Nature 2018

Authors and Affiliations

  1. 1.Department of Computer Science and EngineeringDr. Mahalingam College of Engineering and TechnologyCoimbatoreIndia

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