Semantics-Driven Implicit Aspect Detection in Consumer Reviews

Kim Schouten, Nienke de Boer, Tjian Lam, Marijtje van Leeuwen, Ruud van Luijk, Flavius Frasincar

Abstract: With consumer reviews becoming a mainstream part of e-commerce, a good method of detecting the product or service aspects that are discussed is desirable. This work focuses on detecting aspects that are not literally mentioned in the text, or implicit aspects. To this end, a co-occurrence matrix of synsets from WordNet and implicit aspects is constructed. The semantic relations that exist between synsets in WordNet are exploited to enrich the co-occurrence matrix with more contextual information. Comparing this method with a similar method which is not semantics-driven clearly shows the benefit of the proposed method. Especially corpora of limited size seem to benefit from the added semantic context.