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A New Theoretical Framework for K-Means-Type Clustering
One of the fundamental clustering problems is to assign n points into k clusters based on the minimal sum-of-squares(MSSC), which is known to be...
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The Mathematics of Learning: Dealing with Data *
Learning is key to develo** systems tailored to a broad range of data analysis and information extraction tasks. We outline the mathematical...
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Web Page Classification*
This chapter describes systems that automatically classify web pages into meaningful categories. It first defines two types of web page...
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Clustering Via Decision Tree Construction
Clustering is an exploratory data analysis task. It aims to find the intrinsic structure of data by organizing data objects into similarity groups or...
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Sequential Pattern Mining by Pattern-Growth: Principles and Extensions*
Sequential pattern mining is an important data mining problem with broad applications. However, it is also a challenging problem since the mining may...
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A Feature/Attribute Theory for Association Mining and Constructing the Complete Feature Set
A correct selection of features (attributes) is vital in data mining. For this aim, the complete set of features is constructed. Here are some...
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Incremental Mining on Association Rules
The discovery of association rules has been known to be useful in selective marketing, decision analysis, and business management. An important...
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Web Mining – Concepts, Applications and Research Directions
From its very beginning, the potential of extracting valuable knowledge from the Web has been quite evident. Web mining, i.e. the application of data...
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Mining Association Rules from Tabular Data Guided by Maximal Frequent Itemsets
We propose the use of maximal frequent itemsets (MFIs) to derive association rules from tabular datasets. We first present an efficient method to...
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Privacy-Preserving Data Mining
The growth of data mining has raised concerns among privacy advocates. Some of this is based on a misunderstanding of what data mining does. The...
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Logical Regression Analysis: From Mathematical Formulas to Linguistic Rules
Data mining means the discovery of knowledge from (a large amount of)data, and so data mining should provide not only predictions but also knowledge...
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Technology-Aware Enterprise Modeling: Challenging the Model-Driven Architecture Paradigm
We propose a holistic design approach that extends a traditional Model Driven Architecture paradigm with the bottom-up constraint analysis and...
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Evaluating Large Language Models in Process Mining: Capabilities, Benchmarks, and Evaluation Strategies
Using Large Language Models (LLMs) for Process Mining (PM) tasks is becoming increasingly essential, and initial approaches yield promising results....
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Introducing Agile Controllability in Temporal Business Processes
Dynamic controllability is currently regarded as the most adequate notion for checking the temporal correctness of business processes with temporal...
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Enhancing Research Clarity: Ontology-Based Modeling of Argumentation in RPML
Navigating the research process, from problem identification to argumentation construction, challenges novice researchers. This study introduces RPML...
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A Hierarchical Knowledge Framework for Digital Twins of Buildings and Their Energy Systems (Position Paper)
This position paper explores applying the Data, Information, Knowledge, Wisdom (DIKW) framework to Digital Twins of buildings and their energy...
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Enhancing Our Understanding of Business Process Model Comprehension Using Biometric Data
Much research has been done on the comprehension and development of conceptual models. In related areas such as linguistics and software engineering...
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Could a Large Language Model Contribute Significantly to Requirements Analysis?
This research-in-progress paper presents a quasi-experiment in which three different ChatGPT-4 prompts (for system structure, analysis, and...
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An Explanation User Interface for a Knowledge Graph-Based XAI Approach to Process Analysis
In consulting practice, effective use of AI technologies presupposes consultant’s and client’s ability to understand generated results. Our knowledge...
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A Context-Aware Framework to Support Decision-Making in Production Planning
In the scope of Industry 4.0, this paper showcases the design and implementation of a context-aware decision-making framework that simulates the...