A special lecture seminar was held on October 24, 2024. Details are as follows.

Title ： Intelligent Data Mining and Analysis: A Study of the Utility-Driven Models.

Lecturer ： Dr. Jerry Chun-Wei Lin（Professor in the Department of Distributed Systems and Informatic Devices, Silesian University of Technology, Poland and Western Norway University of Applied Sciences, Norway）

Date ： 13:20〜15:00, October 24 (Thursday), 2024

Place ： Room W305, the 3rd floor, West Building, Koganei Campus

Abstract ： As a large amount of data is collected daily from individuals, businesses and other organizations or applications, various algorithms have been developed to detect interesting and useful patterns in the data that meet a set of requirements specified by a user. The main purpose of data analysis and data mining is to find new, potentially useful patterns that can be used in real-world applications. For example, analyzing customer transactions in a retail store can reveal interesting patterns in customer buying behavior that can then be used for decision-making. In recent years, the demand for utility-based pattern mining and analytics has increased because it can discover more useful and interesting information than simple binary-based pattern mining approaches, which are used in many domains and applications, such as cross-marketing, e-commerce, finance, medicine and biomedicine. In this talk, I will first emphasize the benefits by using the utility-based pattern mining and analysis compared to previous studies (e.g., association rules/frequent itemset mining). Then, I will give a general overview of the state of the art in utility-driven pattern mining and analysis techniques according to three main categories (i.e., data level, constraint level, and application level). Various techniques and modeling on different aspects (levels) of utility-based pattern mining will be presented and reviewed.