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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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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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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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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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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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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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HyperMatch: long-form text matching via hypergraph convolutional networks
Semantic text matching plays a vital role in diverse domains, such as information retrieval, question answering, and recommendation. However, longer...
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Improving laryngeal cancer detection using chaotic metaheuristics integration with squeeze-and-excitation resnet model
Laryngeal cancer (LC) represents a substantial world health problem, with diminished survival rates attributed to late-stage diagnoses. Correct...
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Certifying Accuracy, Privacy, and Robustness of ML-Based Malware Detection
Recent advances in artificial intelligence (AI) are radically changing how systems and applications are designed and developed. In this context, new...
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Automated Detection of Infection in Diabetic Foot Ulcer Using Pre-trained Fast Convolutional Neural Network with U++net
A frequent consequence of diabetes and a significant contributor to morbidity and mortality is diabetic foot ulcer (DFU).Early detection and...
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An Efficient Approach to Reduce Energy Consumption in a Fog Computing Environment Using a Moth Flame Optimization Algorithm
After decades of growth in the computer computing field, cyber-physical systems (CPS), a combination of physical and tangible hardware and virtual...
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Analyzing Data Streams from Cyber-Physical-Systems: A Case Study
We show that conducting a process-mining-centric analysis concerning cyber-physical systems provides insights into usage behavior. To show that, we...
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Designing an Intelligent Contract with Communications and Risk Data
Contract automation is a challenging topic within Artificial Intelligence and LegalTech. From digitised contracts via smart contracts, we are heading...
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Classification and Feature Selection of Alzheimer’s Disease for MRI Data Utilizing Convolutional Neural Network and Support Vector Machine
Alzheimer's disease (AD) is a neurological disease that affect numerous people. According to the literature, forecasting this type of disease can be...
