Semantic Analysis based Customer Reviews Feature Extraction

Abstract

A set of customers’ reviews about restaurants has been analyzed syntactically and semantically for deducing syntactic, contextual and semantic features to leverage the textual similarity metrics. In this paper an approach for rule based extracting semantic features from customer’s reviews have been proposed. The features were extracted based on the knowledge base, co-occurrence and distributional similarity among the reviews’ aspects and descriptors. The approach was applied on the Yelp academic challenges dataset and the results have shown encouraging performance.