Title: Mining fuzzy temporal patterns from process instances with weighted temporal graphs

Authors: R.B.V. Subramanyam, A. Goswami, Bhanu Prasad

Addresses: Department of Computer Science & Engineering, National Institute of Technology Warangal, Andhra Pradesh State, India. ' Department of Mathematics, Indian Institute of Technology Kharagpur, Kharagpur, India. ' Department of Computer and Information Sciences, Florida A&M University, Tallahassee, FL 32307, USA

Abstract: This paper presents an algorithm for mining fuzzy temporal patterns from a given process instance. The fuzzy representation of time intervals embedded between the activities is used for this purpose. Initially, the activities are portrayed with their temporal relationships through temporal graphs and then, the defined data structures are used to retrieve the data suitable for the proposed algorithm. Similar to the familiar k-itemsets and k-dim sequences, their counterparts are introduced in this work. The proposed process-instance level data structure generates an optimum number of temporal itemsets. The proposed algorithm differs from the other existing algorithms on this topic in the representation of the mined data and patterns. An example is provided to demonstrate the algorithm.

Keywords: temporal data mining; fuzzy temporal patterns; weighted temporal graphs; process instance data; temporal itemsets; fuzzy representation; time intervals.

DOI: 10.1504/IJDATS.2008.020023

International Journal of Data Analysis Techniques and Strategies, 2008 Vol.1 No.1, pp.60 - 77

Published online: 21 Aug 2008 *

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