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  Review Paper of Identifying Features in Opinion Mining using Bootstrap Methodology and Naive Bayes Classification  
  Authors : Vishakha I. Sardar; Saroj Date
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Extracting opinion characteristics are based only on models of a single review corpus, ignoring nontrivial disparities in the characteristics of word distribution of the characteristics of opinion across different Corpus. In this article we propose a new method to identify the characteristics of the opinions of online journals by exploiting the difference in opinion statistics through two corpus, a specific corpus of the domain and an independent corpus of the domain the contrasted corpus. We grasp this disparity via a measure called domain relevance (DR), which characterizes the relevance of a term to a collection of texts. First we extract a list of the characteristics of the candidate's opinion of the domain review corpus by defining a set of syntactic dependency rules. For each extracted candidate feature, we then estimate the intrinsic domain (IDR) and extrinsic domain relevance (EDR) scores in the domain-dependent and independent corpus domain, respectively. Candidate characteristics that are less generic (EDR score below a threshold) and more specific for the domain (IDR score higher than another threshold) are confirmed as characteristics of the opinion.


Published In : IJCSN Journal Volume 6, Issue 4

Date of Publication : August 2017

Pages : 509-511

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Vishakha I. Sardar : Dept. of Computer Science and Engineering, MGM’s Jawaharlal Nehru Engineering College Aurangabad, India.

Saroj Date : Dept. of Computer Science and Engineering, MGM’s Jawaharlal Nehru Engineering College Aurangabad, India.


Candidate Feature Extraction, Bootstrap Method, IDR Score, EDR Score, IEDR Score.

In this article, we propose an efficient criterion for the technique of intrinsic and extrinsic domain relevance for the extraction of characteristics. We have used additional dependencies in English grammar to extract features. The weight equation is given to work with real-life reviews. Experimental results showed that the proposed approach yields a much better result than the traditional approach. It is essential that a good independent corpus of the domain is selected. Since this technique relies heavily on disparities in the characteristics of distribution characteristics of opinion, two best thresholds should be selected according to the corpus to improve performance.


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