Abstracting Events for Data Mining

• Main Authors: David LO, RAMALINGAM, Ganesan, RANGANATH, Venkatesh-Prasad, VASWANI, Kapil
• Format: text
• Language: English
• Published: Institutional Knowledge at Singapore Management University 2011
• Subjects: Computer Sciences; Software Engineering
• Online Access: https://ink.library.smu.edu.sg/sis_research/2976; https://ink.library.smu.edu.sg/context/sis_research/article/3976/viewcontent/US20110087700.pdf
• Institution: Singapore Management University

An event is described herein as being representable by a quantified abstraction of the event. The event includes at least one predicate, and the at least one predicate has at least one constant symbol corresponding thereto. An instance of the constant symbol corresponding to the event is identified, and the instance of the constant symbol is replaced by a free variable to obtain an abstracted predicate. Thus, a quantified abstraction of the event is composed as a pair: the abstracted predicate and a mapping between the free variable and an instance of the constant symbol that corresponds to the predicate. A data mining algorithm is executed over abstracted, quantified events to ascertain a correlation between the event and another event.