Natural Language Processing on Diverse Data Layers Through Microservice Architecture

With the rapid growth in Natural Language Processing (NLP), all types of industries find a need for analyzing a massive amount of data. Sentiment analysis is becoming a more exciting area for the businessmen and researchers in Text mining & NLP. This process includes the calculation of various s...

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Bibliographic Details
Published in2020 IEEE International Conference for Innovation in Technology (INOCON) pp. 1 - 6
Main Authors Bhagat, Vandana, J, Bastin Robins
Format Conference Proceeding
LanguageEnglish
Published IEEE 06.11.2020
Subjects
Arrays
Distributed databases
Distributed NLP
Memory
Microservices
Natural language processing
Relational databases
Sentiment analysis
Serverless API
Text Mining
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Summary:With the rapid growth in Natural Language Processing (NLP), all types of industries find a need for analyzing a massive amount of data. Sentiment analysis is becoming a more exciting area for the businessmen and researchers in Text mining & NLP. This process includes the calculation of various sentiments with the help of text mining. Supplementary to this, the world is connected through Information Technology and, businesses are moving toward the next step of the development to make their system more intelligent. Microservices have fulfilled the need for development platforms which help the developers to use various development tools (Languages and applications) efficiently. With the consideration of data analysis for business growth, data security becomes a major concern in front of developers. This paper gives a solution to keep the data secured by providing required access to data scientists without disturbing the base system software. This paper has discussed data storage and exchange policies of microservices through common JavaScript Object Notation (JSON) response which performs the sentiment analysis of customer's data fetched from various microservices through secured APIs.
DOI:10.1109/INOCON50539.2020.9298027