期刊名称：International Journal of Innovative Research in Computer and Communication Engineering
印刷版ISSN：2320-9798
电子版ISSN：2320-9801
出版年度：2017
卷号：5
期号：4
页码：6965
DOI：10.15680/IJIRCCE.2017.0504058
出版社：S&S Publications
摘要：Corpus Data refers to as a collection of huge datasets. Sentiment analysis contributed to a popularresearch area for twitter. The sentiment analysis done without feature extraction fails to give the deep result about theusers opinion but, features of the domain are extracted by building ontology which helps in getting the refinedsentiment analysis. Ontology means a formal, explicit specification of a shared conceptualization. Conceptualizationrefers to an abstract model of some world phenomena. Ontology is used for knowledge sharing and reuse. It improvesinformation organization, management and understanding. In this paper, we have used ontology to analyse the tweets toincrease augmentation and efficiency of sentiments which is obtained using naïve Bayesian algorithm. The work isdone in five stages. In first stage, the tweets are extracted from Twitter4J and stored in a repository. Then sentences areextracted one by one. Sentences extracted are simplified by removing stop words and redundant words. In Secondstage, the words left in the sentences are used for sense matching using WordNet-an online semantic dictionary.WordNet dictionary is used to extract features from tweets. In Third stage, Ontology is being generated by using javacustomized code. Crawler is being designed next to get the details about the automobile domain. The data is stored intext manner. In fourth stage, Mapping of data is done which includes mapping of ontology with the crawler data,together with ontology validation. In fifth stage, Analysis of tweets is done using ontology by applying naïve Bayesianalgorithm and comparison of automobile is done which one is better and what all are the attributes that otherautomobile does not fall into this category.
