Abstract
Private organizations like offices, libraries, and hospitals makes use of computers for computerized database, when computers became a most cost-effective device. After that E.F Codd introduced relational database model, i.e., conventional database. Conventional database can be enhanced to temporal database. Conventional or traditional databases are structured in nature. But always we do not have the pre-organized data. We have to deal with different types of data. That data is huge and in large amount, i.e., big data. Big data mostly emphasized into internal data sources like transaction, log data, emails, etc. From these sources, high-enriched information is extracted by the means of process text data mining or text analytics. In this research work, we will briefly discuss text analytics and its different types and tasks.
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Das, P., Barua, K., Pandey, M., Routaray, S.S. (2019). Context Level Entity Extraction Using Text Analytics with Big Data Tools. In: Abraham, A., Dutta, P., Mandal, J., Bhattacharya, A., Dutta, S. (eds) Emerging Technologies in Data Mining and Information Security. Advances in Intelligent Systems and Computing, vol 813. Springer, Singapore. https://doi.org/10.1007/978-981-13-1498-8_32
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DOI: https://doi.org/10.1007/978-981-13-1498-8_32
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