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Existing personalized recommendation systems are facing many problems such as cold start, data sparseness and high complexity. Users' interests exist more widely and are more personalized compared with purchasing history in traditional recommendation systems. Thus, applying the interest graph in the recommendation process can make up certain shortages. This paper builds the mechanism of a user-interest-goods...
In order to extract class association rules more effectively when dealing with large attributes set, Genetic Network Programming (GNP) based class association rule mining with Attributes Importance has been proposed in this paper. The main difference between the proposed method and the conventional GNP-based class association rule mining is that Attributes Importance is introduced to affect the attributes...
In this paper, we firstly create developer networks by affiliation between projects and developers, and then, with respect to social network analysis, take an approach to empirically study the new developers' behavior and the relationship with the centrality measures. We find that most of new developers choose to cooperate with each other initially, but more collaboration are established between new...
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