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Polish Information Processing Society
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Annals of Computer Science and Information Systems, Volume 9

Position Papers of the 2016 Federated Conference on Computer Science and Information Systems

Identification of Product’s Features Based on Customer Reviews

DOI: http://dx.doi.org/10.15439/2016F372

Citation: Position Papers of the 2016 Federated Conference on Computer Science and Information Systems, M. Ganzha, L. Maciaszek, M. Paprzycki (eds). ACSIS, Vol. 9, pages 25–32 ()

Full text

Abstract. In recent years an e-commerce has become more and more popular. This fact is mainly related to a low cost of running a business, vast access to a large group of potential customers and ease of advertising. Analysis of products' reviews can lead to valuable insights for both customers and manufacturers. Owing to positive reviews a future customer may be convinced to buy the product. A number of reviews for one product can amount to even hundreds what makes it hard for a potential buyer to read them all. The main aim of this paper is to present a method for mining reviews considering products' features, extracting products' features and preparing a summary of reviews. For that purpose a new promising technique - Rule-Based Similarity Model is used. The performance of the algorithm has been verified on online product review articles.

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