Titlebook: Advances in Knowledge Discovery in Databases; Animesh Adhikari,Jhimli Adhikari Book 2015 Springer International Publishing Switzerland 201

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,Oncology—Pancreas and Hepatobiliary System,es of an item over time is an important issue, and therefore, we present the notion of stability of an item. Stable items are useful in making numerous strategic decisions of the company. We have discussed two measures of stability of an item. Based on the degree of stability of an item, an algorith

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,Oncology—Pancreas and Hepatobiliary System,re based on local frequency items. A multi-branch company transacting from different branches often needs to extract global patterns from data distributed over the branches. Global decisions could be made effectively using such patterns. Thus, it becomes important to cluster local frequency items in

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,Oncology—Bone and Soft Tissue Tumors,ant task. Recently, researchers have reported an algorithm for finding calendar-based periodic pattern in a time-stamped data and introduced the concept of certainty factor in association with an overlapped interval. In this chapter, we have extended the concept of certainty factor by incorporating

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,Oncology—Pancreas and Hepatobiliary System,expressing influence of items on other items. In this chapter, we introduce the notion of an overall influence of a set of items on another set of items. We also discuss an extension to the notion of overall association between two items in a database. Using this notion, we have designed two algorit

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,Oncology—Pancreas and Hepatobiliary System,t of view, it might be required to enhance the quality of knowledge synthesized from multiple databases. Also, many decision-making applications are directly based on the available local patterns present in different databases.