Discovering Evolving Temporal Information: Theory and Application to Clinical Databases
نویسندگان
چکیده
منابع مشابه
An approach to discovering multi-temporal patterns and its application to financial databases
Managerial decision-making processes often involve data of the time nature and need to understand complex temporal associations among events. Extending classical association rule mining approaches in consideration of time in order to obtain temporal information/knowledge is deemed important for decision support, which is nowadays one of the key issues in business intelligence. This paper presen...
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Many complex and dynamic database applications such as product modeling and negotiation monitoring require a number of features that have been adopted in semantic models and databases such as active rules, constraints, inheritance, etc. Unfortunately, each feature has largely been considered in isolation. Furthermore, in a commercial negotiation, participants staking their nancial well-beings w...
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The problem of the discovery of association rules comes from the need to discover interesting patterns in transaction data in a supermarket. Since transaction data are temporal we expect to find patterns that depend on time. For example, when gathering data about products purchased in a supermarket, the time of the purchase is stamped in the transaction. In large data volumes, as used for data ...
متن کاملDiscovering during-temporal patterns (DTPs) in large temporal databases
Large temporal Databases (TDBs) usually contain a wealth of data about temporal events. Aimed at discovering temporal patterns with during relationship (during-temporal patterns, DTPs), which is deemed common and potentially valuable in real-world applications, this paper presents an approach to finding such DTPs by investigating some of their properties and incorporating them as desirable prun...
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ژورنال
عنوان ژورنال: SN Computer Science
سال: 2020
ISSN: 2662-995X,2661-8907
DOI: 10.1007/s42979-020-00160-9