UGC Approved Journal no 63975

ISSN: 2349-5162 | ESTD Year : 2014
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Published in:

Volume 6 Issue 6
June-2019
eISSN: 2349-5162

UGC and ISSN approved 7.95 impact factor UGC Approved Journal no 63975

7.95 impact factor calculated by Google scholar

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Published Paper ID:
JETIRDB06001


Registration ID:
221445

Page Number

1-8

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Title

Sentiment Analysis on Amazon Alexa using Big Data Analytics

Abstract

Traditional data analytics systems collect huge static volumes of data and periodically process those data. On the other hand, streaming analytics systems avoid putting data at rest, and process it as it is coming to the system or as it becomes available, cutting the data analytics time significantly and minimizing the time a single data spends in a processing pipeline. In recent years, batch processing was thriving with offline data processing. Both Hadoop and Batch processing have progressed with time to become excellent offline data processing platforms for Big Data. Recently, things have changed drastically, as many use cases across various domains started calling for near-real-time/ real-time response on Big Data for faster decision making in their respective field. Hadoop was not suitable enough for those use cases. The rate at which organizations were analyzing their data was slow, and the data was losing its value exponentially over time. In this project work, the revenue of the company has developed with finding the reviews patterns of the Amazon Alexa among the users by using the following steps: Hadoop installation, Dataset collection, Pre-processing using Chi-Square analysis and how Flume can take log files as source and it can store it directly to file system like HDFS and the Amazon Alexa data analyzation with the implementation of Kafka stream engine in this project work in this research work. This work aims to relate user’s ratings and reviews to discover how beneficial and good a product. User ratings are collected and are analyzed based on different categories (datasets) which gives an insight as to which product performs good and what are the problems associated to a certain non-performing product.

Key Words

Data Mining, Big Data Analytics, Pre-processing, Hadoop Distributed File System, Amazon Alexa, Review Mining, Chi-Square analysis.

Cite This Article

"Sentiment Analysis on Amazon Alexa using Big Data Analytics", International Journal of Emerging Technologies and Innovative Research (www.jetir.org), ISSN:2349-5162, Vol.6, Issue 6, page no.1-8, June 2019, Available :http://www.jetir.org/papers/JETIRDB06001.pdf

ISSN


2349-5162 | Impact Factor 7.95 Calculate by Google Scholar

An International Scholarly Open Access Journal, Peer-Reviewed, Refereed Journal Impact Factor 7.95 Calculate by Google Scholar and Semantic Scholar | AI-Powered Research Tool, Multidisciplinary, Monthly, Multilanguage Journal Indexing in All Major Database & Metadata, Citation Generator

Cite This Article

"Sentiment Analysis on Amazon Alexa using Big Data Analytics", International Journal of Emerging Technologies and Innovative Research (www.jetir.org | UGC and issn Approved), ISSN:2349-5162, Vol.6, Issue 6, page no. pp1-8, June 2019, Available at : http://www.jetir.org/papers/JETIRDB06001.pdf

Publication Details

Published Paper ID: JETIRDB06001
Registration ID: 221445
Published In: Volume 6 | Issue 6 | Year June-2019
DOI (Digital Object Identifier):
Page No: 1-8
Country: -, -, - .
Area: Engineering
ISSN Number: 2349-5162


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