Learn More
Privacy preservation is an important issue in the release of data for mining purposes. The k-anonymity model has been introduced for protecting individual identification. Recent studies show that a more sophisticated model is necessary to protect the association of individuals to sensitive information. In this paper, we propose an (α, k)-anonymity model to(More)
An attribute-oriented induction has been developed in the previous study of knowledge discovery in databases. A concept tree as-cension technique is applied in concept generalization. In this paper, we extend the background knowledge representation from an unconditional non-rule-based concept hierarchy to a rule-based concept hierarchy , which enhances(More)
This article presents a top-down approach for analyzing sequential events in behavioral data. Analysis of behavioral sequential data often entails identifying patterns specified by the researchers. Algorithms were developed and applied to analyze a kind of behavioral data, called discrete action protocol data. Discrete action protocols consist of discrete(More)
Privacy preservation is an important issue in the release of data for mining purposes. The k-anonymity model has been introduced for protecting individual identification. Recent studies show that a more sophisticated model is necessary to protect the association of individuals to sensitive information. In this paper, we propose an (α, k)-anonymity model to(More)
All-to-all broadcasting (Gossiping) is the process of information dissemination in a communication network. Each member in the network has a message to transmit to all other members of the network. We proposed a k-fault-tolerant scheme for a faulty d-dimensional hypercube with n = 2 d nodes where 0 ≤ k < d. The new scheme requires n(n − 1) fewer message(More)
Increasing number of organizations have computing clusters located in different places. The distance between the computing clusters can be quite far apart. The load in one cluster may be very high while the other clusters may have nothing running on the system. A higher throughput can be achieved if load balancing is added between the clusters. In this(More)
INTRODUCTION Association rule mining (Agrawal, Imilienski, & Swami, 1993) has been proposed for understanding the relationships among items in transactions or market baskets. For instance, if a customer buys butter, what is the chance that he/she buys bread at the same time? Such information may be useful for decision makers to determine strategies in a(More)
Frequent pattern discovery in data streams can be very useful in different applications. In time critical applications , a sliding window model is needed to discount stale data. In this paper, we adopt this model to mine the ¡ most interesting itemsets, or to estimate the ¡ most frequent itemsets of different sizes in a data stream. In our method, the(More)
This paper presents a new algorithm for query evaluation for datalog. The algorithm is set-oriented as it uses sets to constraint the arguments of the related rules and the subgoals generated. The nature of the algorithm is top-down with memorization, which captures the fixed-point idea behind the bottom-up approach. We show that the algorithm is(More)