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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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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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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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De-confounding representation learning for counterfactual inference on continuous treatment via generative adversarial network
Counterfactual inference for continuous rather than binary treatment variables is more common in real-world causal inference tasks. While there are...
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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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Gradient-based explanation for non-linear non-parametric dimensionality reduction
Dimensionality reduction (DR) is a popular technique that shows great results to analyze high-dimensional data. Generally, DR is used to produce...
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Examining ALS: reformed PCA and random forest for effective detection of ALS
ALS (Amyotrophic Lateral Sclerosis) is a fatal neurodegenerative disease of the human motor system. It is a group of progressive diseases that...
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TOPCOAT: towards practical two-party Crystals-Dilithium
The development of threshold protocols based on lattice-signature schemes has been of increasing interest in the past several years. The main...
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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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Explainable decomposition of nested dense subgraphs
Discovering dense regions in a graph is a popular tool for analyzing graphs. While useful, analyzing such decompositions may be difficult without...
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Multi-task learning and mutual information maximization with crossmodal transformer for multimodal sentiment analysis
The effectiveness of multimodal sentiment analysis hinges on the seamless integration of information from diverse modalities, where the quality of...
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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...
