Edward Omiecinski

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Mining for a.ssociation rules between items in a large database of sales transactions has been described as an important database mining problem. In this paper we present an efficient algorithm for mining association rules that is fundamentally different from known algorithms. Compared to previous algorithms, our algorithm not only reduces the I/O overhead(More)
Data mining is defined as the process of discovering significant and potentially useful patterns in large volumes of data. Discovering associations between items in a large database is one such data mining activity. In finding associations, support is used as an indicator as to whether an association is interesting. In this paper, we discuss three(More)
Broadcast is a scalable way of disseminating data because broadcasting an item satisfies all outstanding client requests for it. However, because the transmission medium is shared, individual requests may have high response times. In this paper, we show how to minimize the average response time given multiple broadcast channels by optimally partitioning(More)
Mining for association rules between items in a large database of sales transactions has been described as an important database mining problem. In this paper we present an eecient algorithm for mining association rules that is fundamentally diierent from known algorithms. Compared to the previous algorithms, our algorithm reduces both CPU and I/O(More)
Mining for association rules is considered an important data mining problem. Many diierent variations of this problem have been described in the literature. In this paper we introduce the problem of mining for negative associations. A naive approach to nding negative associations leads to a very large number of rules with low interest measures. We address(More)
Multiple-disk I/O systems (Disk Arrays) have been an attractive approach to meet high performance I/O demands in data intensive applications such as information retrieval systems. When we partition and distribute les across multiple disks to exploit the potential for I/O parallelism, a balanced I/O workload distribution becomes important for good(More)
While the desire to support fast, ad hoc query processing for large data warehouses has motivated the recent introduction of many new indexing structures, with a few notable exceptions (namely, the LSM-Tree [4] and the Stepped Merge Method [1]) little attention has been given to developing new indexing schemes that allow fast insertions. Since additions to(More)
In this paper, we propose techniques for scheduling data broadcasts that are favorable in terms of both response and tuning time. In other words, these techniques ensure that a typical data request will be quickly satisfied and its reception will require a low client-side energy expenditure. By generating broadcast schedules based on Acharya et al.’s(More)
Mining trajectory data has been gaining significant interest in recent years. However, existing approaches to trajectory clustering are mainly based on density and Euclidean distance measures. We argue that when the utility of spatial clustering of mobile object trajectories is targeted at road network aware location based applications, density and(More)