Multi Layered Rule-Based Technique for Explicit Aspect Extraction from Online Reviews

Abstract

Aspect is a feature of product, about which the user is expressing his/her opinion. In the field of sentiment analysis, the key task is to extract aspects or opinion targets from blogs, product reviews or discussions, users have expressed their opinions about a product. Extracting just positive or negative opinion is not much useful without knowing the targeted Aspect or Feature. If the aspect or feature is explicitly mentioned in the user‘s review, that aspect is called explicit aspect, otherwise it is termed as implicit aspect. Extracting explicit aspects from the opinion statements has been an active area of research. To achieve this milestone, multiple methodologies have been developed including supervised, rule-based and unsupervised approaches. Many researchers used dependency relation of the sentence also called syntactical dependencies to formulate the rules for aspect extraction. However this approach heavily depends on the authenticity of the employed POS tagger and dependency parser. Their outputs can be misleading as the users may not follow the grammatical rules strictly while writing their opinions. Another popular approach for explicit aspect extraction is sequential rules based approach, wherein the rules are formed by learning from user‘s behavior. However, in general, the sequential rule-based approaches have poor generalization capability. Moreover, existing approaches mostly considers the aspects as noun or noun phrase, so these approaches are unable to extract verb aspects. In this thesis, for overcoming the said problems with the existing approaches, we have proposed a multi-layered rule-based (ML-RB) technique using the syntactic dependency parser based rules along with some selective sequential rules. These rules are applied one after another (i.e. sequential rules after syntactic rules) for extracting noun explicit aspects form customer‘s reviews, thereby forming layers of the application. We also have crafted rules for extraction of verb aspects after rigorous analysis. In third layer, x we have used these verb rules, which are primarily based on the association among verb and opinion words. The proposed multi-layer technique compensates for the weaknesses of individual layers and yields improved results. As the proposed approach has capability to extract both noun and verb aspect, it has better Recall and F1-score on two publically available bench mark customer review datasets, as compared to other famous approaches