Natural Language Processing ( Nlp )

7704 Words Jul 20th, 2015 31 Pages
CHAPTER1: INTRODUCTION

Natural Language Processing (NLP) deals with actual text element processing. The text element is transformed into machine format by NLP. Artificial Intelligence (AI) uses information provided by the NLP and applies a lot of maths to determine whether something is positive or negative. Several methods exist to determine an author’s view on a topic from natural language textual information. Some form of machine learning approach is employed and which has varying degree of effectiveness. One of the types of natural language processing is opinion mining which deals with tracking the mood of the people regarding a particular product or topic. This software provides automatic extraction of opinions, emotions and sentiments in text and also tracks attitudes and feelings on the web. People express their views by writing blog posts, comments, reviews and tweets about all sorts of different topics. Tracking products and brands and then determining whether they are viewed positively or negatively can be done using web. The opinion mining has slightly different tasks and many names, e.g. sentiment analysis, opinion extraction, sentiment mining, subjectivity analysis, affect analysis, emotion analysis, review mining, etc.
However, they all come under the umbrella of sentiment analysis or opinion mining. Sentiment classification, feature based sentiment classification and opinion summarization are few main fields of research predominate in sentiment analysis.
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