Context Aware Recommender System for Online Grocery Markets in Indonesia
Abstract
Creating superior customer experience seems to be one of the central objectives in today’s retailing environments. Retailers around the globe have embraced the concept of customer experience management, with many incorporating the notion into their mission statements. It is necessary to establish an online platform that helps customers search products, compare prices and indicate their location. The primary step is classifying and examining some influencing factors for online purchases, so examining those factors that influence consumers' behavior via the internet is vital. Information retrieval techniques have matured with time and search engines have done a great job in indexing online content. A recommender system aims to provide users with personalized online product or service recommendations to handle the increasing online information overload problem. The goal of personalization is to provide users with what they want or need without requiring them to ask for it explicitly. This is a literature based review study. To facilitate development of the system a high quality, instructive review of current trends is conducted, not only of the theoretical research results but more importantly of the practical developments in recommender systems. This paper reviews up-to-date application developments of recommender systems and clusters their applications. It systematically examines the reported recommender systems through four dimensions: recommendation methods (such as CF), recommender systems software (such as BizSeeker), real-world application domains (such as e-business) and application platforms (such as mobile-based platforms).
Key words: Context Aware Recommender System, Online Grocery Markets, Indonesia
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