Multidimensional Filtering Approach Based on Contextual Information

Existing recommended systems offer calculation of recommendation for user-item with e-commerce. But these systems omit much available information. It is user's contextual information. Thus accuracy of recommender systems is relatively lower. Mostly excepted information is difficult to clearly define the attributes and to calculate the values as the numerical data. If this contextual information can be changed into calculable element in recommender system, it can become the improved recommendation technique. This paper proposes multidimensional approach additionally applying contextual information for 2 dimensions based on existing recommendation system

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