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Current top-N recommendation methods compute the recommendations by taking into account only relations between pairs of items, thus leading to potential unused information when higher-order relations between the items exist. Past attempts to incorporate the higherorder information were done in the context of neighborhood-based methods. However, in many(More)
This paper suggests a number of research directions in which the recommender systems can improve their quality, by moving beyond the assumptions of linearity and independence that are traditionally made. These assumptions, while producing effective and meaningful results, can be suboptimal, as in lots of cases they do not represent the real datasets. In(More)
Sales professionals help organizations win clients for products and services. Generating new clients starts with identifying the right decision makers at the target organization. For the past decade, online professional networks have collected tremendous amount of data on people's identity, their network and behavior data of buyers and sellers building(More)
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