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Text Analytics in Ecommerce Platforms for Product Managers

Madhumathi S.*, Gomathi R. **

*-** Department of Computer Science and Engineering, Bannari Amman Institute of Technology, Sathyamangalam, Tamil Nadu, India.

Periodicity:September - November'2020
DOI : https://doi.org/10.26634/jit.9.4.18106

Abstract

The work flow model can be implemented with data mining in the E-commerce platforms. It helps the product/project manager in several ways. The multiple queries have been figured out and have been solved here. The data and reviews are generated automatically. The text are generated with web crawler and stored in database as raw data. The data are cleaned with Natural Language Processing methods and algorithms. The specific types of algorithms are digitally defined for this framework. The specific type of algorithm is run for specific new cases in different platforms. This is designed in a manner to be used by humans for the interaction purpose. Python is used for pulling data out of files. The process gets automated and the data is cleaned to attain the efficiency. The data review has been taken and classified with the data cleaning process with Natural Language Processing. The Natural Language Processing techniques used, are Sentimental Analysis, Topic Modeling and Text Generation.

Keywords

Big data, Natural Language Processing, Pre-analyzed, Kinesis Stream, Lambda Function, Data.

How to Cite this Article?

Madhumathi, S., and Gomathi, R. (2020). Text Analytics in Ecommerce Platforms for Product Managers. i-manager's Journal on Information Technology, 9(4), 23-28. https://doi.org/10.26634/jit.9.4.18106

References

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