Current trends on Context Based Retrieval of Sarcastic Sentiment approach of past on Big Data

Abstract

Information retrieval has suit for mainly needed in the recent trend in information periods. Take possession of information retrieval is   more difficult of the data multiplicity and unconventional ways of data dissemination. This paper presents a context based sarcastic comments of text in information retrieval architecture to perform real time retrieval of data. This is a review about the operates on the semantic similarity of the data, rather than the content similarity. This paper review the methods have review of the work which exhibits better and capable of retrieval levels supports high trustworthy. The retrieved sarcastic text documents are pre-processed and feature vectors are created from the tokens. Polarity matching is applied to filter semantically connected outputs and magnitude based result valued of priority is functions upon further elimination of inappropriate results. The paper conducted using the past proposed model exhibits how the results show the retrieval rates, along with high precision and recall levels exhibiting the efficient of classifier super vector model training the datas work.

 Keywords-NaviBias,Sarcast,Precision ,Spark, Hadoop