B. Narendra

Work place: CSSE, SVEC, Tirupati, A.P, India

E-mail: bnarendracse@gmail.com


Research Interests: Pattern Recognition, Speech Synthesis, Data Mining, Data Structures and Algorithms


Mr. B. Narendra, Completed his M.Tech from JNTUA, Currently working as Asst. Professor, CSSE, SVEC. His areas of interest include cloud computing, Data mining, pattern synthesis and machine learning. He published papers in various journals

Author Articles
Sentiment Analysis on Movie Reviews: A Comparative Study of Machine Learning Algorithms and Open Source Technologies

By B. Narendra K. Uday Sai G. Rajesh K. Hemanth M. V. Chaitanya Teja K. Deva Kumar

DOI: https://doi.org/10.5815/ijisa.2016.08.08, Pub. Date: 8 Aug. 2016

Social Networks such as Facebook, Twitter, Linked In etc… are rich in opinion data and thus Sentiment Analysis has gained a great attention due to the abundance of this ever growing opinion data. In this research paper our target set is movie reviews. There are diverge range of mechanisms to express their data which may be either subjective, objective or a mixture of both. Besides the data collected from World Wide Web consists of lot of noisy data. It is very much true that we are going to apply some pre-processing techniques and compare the accuracy using Machine Learning algorithm Naïve Bayes Classifier. With ever growing demand to mine the Big Data the open source software technologies such as Hadoop using map reducing paradigm has gained a lot of pragmatic importance. This paper illustrates a comparitive study of sentiment analysis of movie reviews using Naïve Bayes Classifier and Apache Hadoop in order to calculate the performance of the algorithms and show that Map Reduce paradigm of Apache Hadoop performed better than Naïve Bayes Classifier.

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Loss Less and Privacy Preserved Data Retrieval in Cloud Environment using TRSE

By T. Kavitha B. Narendra K.Thejaswi P. Nageswara Rao

DOI: https://doi.org/10.5815/ijwmt.2015.06.03, Pub. Date: 8 Nov. 2015

In the modern era of the computing world, the data producing and using it is becoming large and instant at various places. For availing the data at different locations for processing we need to store it in the global platform. Cloud environment provides a best and easy way for this. Cloud computing is becoming as the essential thing for high-quality data services. However there are some potential problems with respect to data security. Here encryption techniques can be used for providing security, but with restricted efficiency. In this paper we propose a new encryption mechanism for providing data security in cloud environment. We propose a two round searchable encryption which supports multi keyword retrieval. Here we adapted a vector space model for improving search accuracy; the elgamal encryption technique allows users to involve in the ranking, while the essential key part of encryption will be done at the source itself. The proposed improves the data security and reduces data leakage.

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Other Articles