2,762 Result(s)
within
Data Mining and Knowledge Discovery
Information Systems Applications (incl. Internet)
Ke** Zhang
Chapter
Conference Paper
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Chapter and Conference Paper
Multi-view EM Algorithm for Finite Mixture Models
In this paper, Multi-View Expectation and Maximization (EM) algorithm for finite mixture models is proposed by us to handle real-world learning problems which have natural feature splits. Multi-View EM does fe...
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Chapter and Conference Paper
A Bayesian Method for High-Frequency Restoration of Low Sample-Rate Speech
Compared with high sample-rate speeches, low sample-rate speeches lose all high frequency components that outrange the Nyquist frequency, which might severely impair the speeches’ sound effects. To address thi...
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Chapter and Conference Paper
Feature Extraction for Handwritten Chinese Character by Weighted Dynamic Mesh Based on Nonlinear Normalization
This paper describes a new feature extraction method contributing to improvement of the performance of a handwritten Chinese character recognition system. By using enhanced weighted dynamic meshes based on non...
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Chapter and Conference Paper
Spectral Clustering for Time Series
This paper presents a general framework for time series clustering based on spectral decomposition of the affinity matrix. We use the Gaussian function to construct the affinity matrix and develop a gradient b...
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Chapter and Conference Paper
Enhancing DWT for Recent-Biased Dimension Reduction of Time Series Data
In many applications, old data in time series become less important as time elapses, which is a big challenge to traditional techniques for dimension reduction. To improve Discrete Wavelet Transform (DWT) for ...
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Chapter and Conference Paper
Logical Properties of Belief-Revision-Based Bargaining Solution
This paper explores logical properties of belief-revision-based bargaining solution. We first present a syntax-independent construction of bargaining solution based on prioritized belief revision. With the con...
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Chapter and Conference Paper
Training Classifiers for Unbalanced Distribution and Cost-Sensitive Domains with ROC Analysis
ROC (Receiver Operating Characteristic) has been used as a tool for the analysis and evaluation of two-class classifiers, even the training data embraces unbalanced class distribution and cost-sensitiveness. H...
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Chapter and Conference Paper
Protein Folding Prediction Using an Improved Genetic-Annealing Algorithm
Based on the off-lattice AB model consisting of hydrophobic and hydrophilic residues, a novel hybrid algorithm is presented for searching the ground-state conformation of the protein. This algorithm combines gene...
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Chapter and Conference Paper
Extracting Minimum Unsatisfiable Cores with a Greedy Genetic Algorithm
Explaining the causes of infeasibility of Boolean formulas has practical applications in various fields. We are generally interested in a minimum explanation of infeasibility that excludes irrelevant informati...
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Chapter and Conference Paper
Customer Online Shop** Behaviours Analysis Using Bayesian Networks
This study applies Bayesian network technique to analyse the relationships among customer online shop** behaviours and customer requirements. This study first proposes an initial behaviour-requirement relati...
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Chapter and Conference Paper
GP for Object Classification: Brood Size in Brood Recombination Crossover
The brood size plays an important role in the brood recombination crossover method in genetic programming. However, there has not been any thorough investigation on the brood size and the methods for setting t...
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Chapter and Conference Paper
Cancer Classification by Kernel Principal Component Self-regression
The classification of cancer based on gene expression data is one of the most important tasks in bioinformatics, and is essential for future clinical implementations of microarray based cancer diagnosis. In th...
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Chapter and Conference Paper
A Bayesian Network Approach to Multi-feature Based Image Retrieval
This paper aims at devising a Bayesian Network approach to object centered image retrieval employing non-monotonic inference rules and combining multiple low-level visual primitives as cue for retrieval. The i...
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Chapter and Conference Paper
Selection for Feature Gene Subset in Microarray Expression Profiles Based on an Improved Genetic Algorithm
It is an important subject to extract feature genes from microarray expression profiles in the study of computational biology. Based on an improved genetic algorithm (IGA), a feature selection method is propos...
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Chapter and Conference Paper
TreeWrapper: Automatic Data Extraction Based on Tree Representation
This paper introduces a new algorithm that learns to extract data from Web pages with relatively regular data structures. Current existing systems require training on either manually labelled pages or at least...
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Chapter and Conference Paper
Quotient Space Based Multi-granular Analysis
We presented a quotient space model that can represent a problem at different granularities; each model has three components: the universe X, property f and structure T. So a multi-granular analysis can be imp...
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Chapter and Conference Paper
Cost-Time Sensitive Decision Tree with Missing Values
Cost-sensitive decision tree learning is very important and popular in machine learning and data mining community. There are many literatures focusing on misclassification cost and test cost at present. In rea...
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Chapter and Conference Paper
Irregular Behavior Recognition Based on Two Types of Treading Tracks Under Particular Scenes
Visual analysis of human motion from video sequences is one of the most active research topics in the field of computer vision. This research has certain practical value and can be widely applied in some place...
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Chapter and Conference Paper
Class Association Rule Mining with Multiple Imbalanced Attributes
In this paper, we propose a novel framework to deal with data imbalance in class association rule mining. In each class association rule, the right-hand is a target class while the left-hand may contain one or...
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Chapter and Conference Paper
Semplore: An IR Approach to Scalable Hybrid Query of Semantic Web Data
As an extension to the current Web, Semantic Web will not only contain structured data with machine understandable semantics but also textual information. While structured queries can be used to find informati...
