Browsing by Author "Saygin, Y."

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Open Access
Automated construction of fuzzy event sets and its application to active databases
(IEEE, 2001) Saygin, Y.; Ulusoy, Özgür
Fuzzy sets and fuzzy logic research aims to bridge the gap between the crisp world of math and the real world. Fuzzy set theory was applied to many different areas, from control to databases. Sometimes the number of events in an event-driven system may become very high and unmanageable. Therefore, it is very useful to organize the events into fuzzy event sets also introducing the benefits of the fuzzy set theory. All the events that have occurred in a system can be stored in event histories which contain precious hidden information. In this paper, we propose a method for automated construction of fuzzy event sets out of event histories via data mining techniques. The useful information hidden in the event history is extracted into a matrix called sequential proximity matrix. This matrix shows the proximities of events and it is used for fuzzy rule execution via similarity based event detection and construction of fuzzy event sets. Our application platform is active databases. We describe how fuzzy event sets can be exploited for similarity based event detection and fuzzy rule execution in active database systems.
Open Access
Exploiting data mining techniques for broadcasting data in mobile computing environments
(IEEE, 2002) Saygin, Y.; Ulusoy, Özgür
Mobile computers can be equipped with wireless communication devices that enable users to access data services from any location. In wireless communication, the server-to-client (downlink) communication bandwidth is much higher than the client-to-server (uplink) communication bandwidth. This asymmetry makes the dissemination of data to client machines a desirable approach. However, dissemination of data by broadcasting may induce high access latency in case the number of broadcast data items is large. In this paper, we propose two methods aiming to reduce client access latency of broadcast data. Our methods are based on analyzing the broadcast history (i.e., the chronological sequence of items that have been requested by clients) using data mining techniques. With the first method, the data items in the broadcast disk are organized in such a way that the items requested subsequently are placed close to each other. The second method focuses on improving the cache hit ratio to be able to decrease the access latency. It enables clients to prefetch the data from the broadcast disk based on the rules extracted from previous data request patterns. The proposed methods are implemented on a Web log to estimate their effectiveness. It is shown through performance experiments that the proposed rule-based methods are effective in improving the system performance in terms of the average latency as well as the cache hit ratio of mobile clients.
Open Access
Using unknowns to prevent discovery of association rules
(2001) Saygin, Y.; Verykios V.S.; Clifton, C.
Data mining technology has given us new capabilities to identify correlations in large data sets. This introduces risks when the data is to be made public, but the correlations are private. We introduce a method for selectively removing individual values from a database to prevent the discovery of a set of rules, while preserving the data for other applications. The efficacy and complexity of this method are discussed. We also present an experiment showing an example of this methodology.