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The Vector Space Model has been and to a great extent still is the de facto choice for profile representation in contentbased Information Filtering. However, user profiles represented as weighted keyword vectors have inherent dimensionality problems. As the number of profile keywords increases, the vector representation becomes ambiguous, due to the exponential increase in the volume of the vector space and in the number of possible keyword combinations. We argue that the complexity anddoi:10.1145/1835449.1835485 dblp:conf/sigir/NanasVR10 fatcat:y27kbjl2d5g2beg5xfhqivprve