Mining High Utility Patterns Over Data Streams

Morteza Zihayat
January 2016

Abstract

This paper presents comprehensive methods for mining high utility patterns over data streams, addressing the challenges of real-time pattern discovery.

Type
Journal article
Publication
Journal Article

This work provides comprehensive coverage of high utility pattern mining in streaming data.

Data Mining Data Streams High Utility Patterns Pattern Mining Real-Time Processing
Morteza Zihayat
Morteza Zihayat
Principal Investigator

Dr. Morteza Zihayat is a Canada Research Chair (CRC) in Human-Centered AI and Associate Professor at Toronto Metropolitan University, Faculty of Engineering and Architectural Science. He also holds appointments as Adjunct Associate Professor at the University of Waterloo (Management Sciences) and IBM Faculty Fellow at IBM Centre for Advanced Studies. He is the Director of the Human-Centered Machine Intelligence Lab.