Sentiment Analysis of Telugu data and comparing advanced ensemble techniques using different text processing methods

被引：1

作者：

Boddupalli, Srikiran ^{[1
]}

Saranya, Anitha Sai ^{[1
]}

Mundra, Usha ^{[1
]}

Dasam, Pratyusha ^{[1
]}

Sriram, Padmamala ^{[1
]}

机构：

[1] Amrita Vishwa Vidyapeetham, Comp Sci & Engn, Amritapuri, India

来源：

2019 5TH INTERNATIONAL CONFERENCE ON COMPUTING, COMMUNICATION, CONTROL AND AUTOMATION (ICCUBEA) | 2019年

关键词：

Sentiment Analysis; Binary Classification; Advanced ensemble techniques; tf-idf;

D O I：

10.1109/iccubea47591.2019.9128877

中图分类号：

TP [自动化技术、计算机技术];

学科分类号：

0812 ;

摘要：

Predicting or classifying a particular sentence or review is very important for companies to launch or upgrade their products. As customers comment, review or express their views via social media. Sentiment analysis plays a crucial role in this process by analyzing reviews, comments etc. The two classes under binary classification are positive and negative. The positive class shows a good note and the negative class shows a bad note. A valid method for predicting sentiments could enable us to pull out opinions from the internet and predict customers taste. In this paper, we compare advanced ensemble techniques and we brief where we can improve our algorithm.

引用

页数：6

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