Abstract

In recent years, the remarkableexpansion of web technologies, lead to an massive quantity of user generated information in online systems.This large amount of information on web platforms make them viable for use as data sources, in applications based on opinion mining and sentiment analysis.Sentiment analysishas become a vital part in today's era.Post massiveexpansion of web technology, reviews existing on net are in surplus quantity.It wouldbe more helpful to an individual or organization if these opinions serve accurate sentiment of the whole review/document.This paper implements naïve Bayes algorithm to categorize the sentence in positive, negative and neutral precisely.So,weexecuted the proposed technique and we evaluated its performance, and suggested instructions of enhancement.

Keywords:
Naive Bayes classifier Artificial intelligence Computer science Bayes' theorem Sentiment analysis Bayes classifier Pattern recognition (psychology) Bayesian probability Support vector machine

Metrics

10
Cited By
0.00
FWCI (Field Weighted Citation Impact)
14
Refs
0.36
Citation Normalized Percentile
Is in top 1%
Is in top 10%

Citation History

Topics

Sentiment Analysis and Opinion Mining
Physical Sciences →  Computer Science →  Artificial Intelligence
Text and Document Classification Technologies
Physical Sciences →  Computer Science →  Artificial Intelligence
Advanced Text Analysis Techniques
Physical Sciences →  Computer Science →  Artificial Intelligence

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