Titlebook: Discovery Science; 10th International C Vincent Corruble,Masayuki Takeda,Einoshin Suzuki Conference proceedings 2007 Springer-Verlag Berlin

FIN

On Approximating Minimum Infrequent and Maximum Frequent Setsem) set mining. Gunopulos et al. [10] have shown that finding a maximum frequent set is .-hard. In this paper I show that the minimization problem is also .-hard. As a next step I investigate whether these problems can be approximated. While a simple greedy algorithm turns out to approximate a minim

Insul島

A Partially Dynamic Clustering Algorithm for Data Insertion and Removalnts classification, etc. The goal is to efficiently maintain homogenous and well-separated clusters as new data are inserted or existing data are removed. We propose a framework called .based solely on pairwise dissimilarities among all pairs of data and on cluster dominance. In experiments on bench

不安

Positivism Against Constructivism: A Network Game to Learn Epistemologypistemology, as traditional science teaching is mostly dogmatic and based on contents. Previous studies show that pupils, science students and teachers mostly own positivist and realist spontaneous conceptions of science and scientific discovery. Here, we present the evaluation of the didactic impac

折磨

Learning Locally Weighted C4.4 for Class Probability Estimationct marketing, we often need to deploy different promotion strategies to customers with different likelihood (probability) of buying some products. When our learning task is to build a model with accurate class probability estimations, C4.4 is the most popular one for achieving this task because of i

幻影

啜泣

微不足道

Maximizer

極為憤怒

BAIL

A Consequence Finding Approach for Full Clausal Abduction. But few methods can exploit the full potential of clausal logic and abduce non-ground explanations with indefinite answers. This paper shows how the consequence finding method of Skip Ordered Linear (SOL) resolution can overcome the limitations of existing systems by proposing a method that is sou