Open AccessFramework for High Utility Pattern Mining using Dynamically Generated Minimum Support ThresholdFramework for High Utility Pattern Mining using Dynamically Generated Minimum Support Threshold
Author(s) -
Shankar B. Naik,
Jyoti D. Pawar
Publication year - 2018
Publication title -
international journal of engineering and technology
Language(s) - English
Resource type - Journals
ISSN - 2227-524X
DOI - 10.14419/ijet.v7i4.19.28276
Subject(s) - computer science , data mining , data stream mining , sliding window protocol , data stream , window (computing) , threshold limit value , telecommunications , operating system , medicine , environmental health
In this paper we have proposed a framework which uses high utility itemset mining to store data stream elements in a compressed form and then detect events from the sliding window. This approach promises to reduce the memory requirements when applied to frequent pattern mining in data streams.In addition to this, a method to dynamically define the value of minimum support threshold based on data in the data stream is presented.