Identification of Features from User Opinions using Domain Relevance

Identification of opinion features from online user reviews is a task to identify on which feature user is going to put his opinion. There are number of existing techniques for opinion feature identification but, they are extracting features from a single corpus [2]. These techniques ignore the non trivial disparities in distribution of words of opinion features across two or more corpora. This work discusses a novel method for opinion feature identification from online reviews by evaluation of frequencies in two corpora, one is domain-specific and other is domain-independent corpus. This distribution is measured by using domain relevance [12]. The first task of this work is the identify candidate features in user reviews by applying a set of syntactic rules. The second step is to measure intrinsic-domain relevance and extrinsic-domain relevance scores on the domain dependent and domain-independent corpora respectively. The third step is to extract candidate features that are less generic and more domain specific, are then conformed as opinion features. This approach is called as intrinsic extrinsic domain relevance. DOI: 10.17762/ijritcc2321-8169.150611

Research Directions, Challenges and Issues in Opinion Mining

Rapid growth of Internet and availability of user reviews on the web for any product has provided a need for an effective system to analyze the web reviews. Such reviews are useful to some extent, promising both the customers and product manufacturers. For any popular product, the number of reviews can be in hundreds or even thousands. This creates difficulty for a customer to analyze them and make important decisions on whether to purchase the product or to not. Mining such product reviews or opinions is termed as opinion mining which is broadly classified into two main categories namely facts and opinions. Though there are several approaches for opinion mining, there remains a challenge to decide on the recommendation provided by the system. In this paper, we analyze the basics of opinion mining, challenges, pros & cons of past opinion mining systems and provide some directions for the future research work, focusing on the challenges and issues