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This paper has three primary research contributions:
- Analysis of the item-based prediction algorithms and
identification of different ways to implement its subtasks.
- Formulation of a precomputed model of item similarity to
increase the online scalability of item-based recommendations.
- An experimental comparison of the quality of several different
item-based algorithms to the classic user-based (nearest neighbor)
Badrul M. Sarwar