No abstract

No abstract

No abstract

In many E-commerce sites, recommender systems, which provide personalized recommendation from among a large number of items, are recently introduced. Collaborative ltering is one of the most successful algorithms which provide recommendations using ratings of users on items. There are two approaches such as user-based and item-based collaborative ltering. Additionally a unifying method for userbased and item-based collaborative ltering was proposed to improve the recommendation accuracy.The unifying approach uses a constant value as a weight parameter to unify both algorithms. However, because the optimal weight for unifying is actually dierent by the situation, the algorithm should estimate an appropriate weight dynamically, and should use it. In this research, rst, we investigated the relationship between recommendation accuracy and the weight parameter. The results show the optimal weight is dierent depending on the situation. Second, we propose an approach for estimation of the appropriate weight value based on collected ratings. Then, we discussed the eectiveness of the proposed approach based on both multi-agent simulation and MovieLens dataset. The results show that the proposed approach can estimate the weight value within an error rate of 0.5% for the optimal weight.

Potassium 3-aminopropylamide, readily prepared in situ from K H and 3-aminopropylamine, effects rapid, multipositional isomerization of the triple bond in prop-2-ynylic and other acetylenic alcohols t o the chain terminus remote from the hydroxy function, within minutes at 0-20 "C.