14 articles for “Customer Classification”

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Literature ReviewOpen accessIn the abstractOverview and Future Opportunities of Sentiment Analysis Approaches for Big DataNurfadhlina Mohd Sharef, Harnani Mat Zin, Samaneh NadaliThe ability to exploit public sentiment in social media is increasingly considered as an important tool for market understanding, customer segmentation and stock price prediction for strategic marketing planning and manoeuvring. This evolution of technology adoption is energised by the healthy growth in big data framework, which caused applications based on Sentiment Analysis (SA) in big data to become common … …Journal of Computer Science, Vol. 12, Issue 3 · 26 Apr 2016 · 10,313 accessesView PDF Cite

Research ArticleOpen accessIn the abstractA Novel Approach for User Navigation Pattern Discovery and Analysis for Web Usage MiningJ. Vellingiri, S. Kaliraj, S. Satheeshkumar, T. ParthibanWebsites on the internet are useful source of information in our day-to-day activity. Web Usage Mining (WUM) is one of the major applications of data mining, artificial intelligence and so on to the web data to predict the user's visiting behaviours and obtains their interests by analyzing the patterns. WUM has turned out to be one of the considerable areas … …Journal of Computer Science, Vol. 11, Issue 2 · 17 Sep 2014 · 7,630 accessesView PDF Cite

Research ArticleOpen accessIn the abstractAN AGENT BASED FRAMEWORK FOR SENTIMENT CLASSIFICATION OF ONLINE REVIEWS USING ONTOLOGYP. Kalaivani, K. L. ShunmuganathanIn this study, we design and develop an agent based framework for sentiment classification of online reviews using ontology. The book review ranking is based on the sentiment classification result. We propose a novel approach with the help of the JADE platform to solve problems by non-visual automatic sentiment classification. The description of book reviews ranking are generated from the … …Journal of Computer Science, Vol. 10, Issue 5 · 15 Jan 2014 · 6,744 accessesView PDF Cite

Research ArticleOpen accessAll words, across the recordEvaluation of Customer Behaviour Irregularities in Cameroon Electricity Network using Support Vector MachineLekini Nkodo Claude Bernard, Ndzana Benoît, Oumarou HamandjodaNon-Technical Losses (NTLs) in the Cameroonians electricity network are approximately 30 to 40% of production and are estimated at several billion CFA francs per year for National Electricity Company (ENEO); Hence the importance of finding effective solutions to fight against these losses. The purpose of this work was to develop a tool for the fraud detection for Cameroon National Electricity … …American Journal of Engineering and Applied Sciences, Vol. 10, Issue 1 · 6 Jan 2017 · 7,544 accessesView PDF Cite