SENTIMENTAL ANALYSIS WITH BIGDATA USING HADOOP
International Journal of Computer Science (IJCS) Published by SK Research Group of Companies (SKRGC)
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Abstract
Big data is the term for a collection of data sets which are large and complex, it contain structured and unstructured both type of data. Data comes from everywhere, sensors used to gather climate information, posts to social media sites, digital pictures and videos etc. This data is known as big data. The proliferation of textual data in business is overwhelming. Unstructured textual data is being constantly generated via call center logs, emails, documents on the web, blogs, tweets, customer comments, customer reviews, and so on. While the amount of textual data is increasing rapidly, businesses’ ability to summarize, understand, and make sense of such data for making better business decisions remain challenging. This paper takes a quick look at how to organize and analyze textual data for extracting insightful customer intelligence from a large collection of documents and for using such information to improve business operations and performance.
References
1. Berry, M.andLinoff, G., Master Data Mining: The Art and Science of Customer Relationship Management, Wiley publisher, 2000.
2. Fayadd, U., Piatesky -Shapiro, G., and Smyth, P, From Data Mining To Knowledge Discovery in Databases”, The MIT Press, ISBN 0–26256097–6, Fayap, 1996.
3. Gorunescu, F, Data Mining: Concepts, Models, and Techniques, Springer, 2011.
4. Han, J., and Kamber, M. ,Data mining: Concepts and techniques, Morgan-Kaufman Series of Data Management Systems San Diego:Academic Press, 2001.
5. Heikki, Mannila, Data mining: machine learning, statistics and databases, IEEE, 1996.
6. Jing He,Advances in Data Mining: History and Future, Third international Symposium on Information Technology Application, 978-0-7695- 3859-4, IEEE, 2009.
7. Kubick, W.R.: Big Data, Information and Meaning. In: Clinical Trial Insights, pp. 26–28 (2012)
8. NeelamadhabPadhy, Dr. Pragnyaban Mishra and RasmitaPanigrahi, “The Survey of Data Mining Applications and Feature Scope, International Journal of Computer Science, Engineering and Information Technology (IJCSEIT)”, vol.2, no.3, June
9. Piatetsky-Shapiro, Gregory, The Data-Mining Industry Coming of Age,”IEEE Intelligent Systems, 2000.
10. Russom, P.: Big Data Analytics. In: TDWI Best Practices Report, pp. 1–40 (2011).
Keywords
Big Data, Hadoop, Sentimental Analysis
