Advanced Data Mining and Applications [electronic resource] : 6th International Conference, ADMA 2010, Chongqing, China, November 19-21, 2010, Proceedings, Part II /
Cao, Longbing.editor.
Feng, Yong.editor.
Zhong, Jiang.editor.
With the ever-growing power of generating, transmitting, and collecting huge amounts of data, information overloadis nowan imminent problemto mankind. The overwhelming demand for information processing is not just about a better understanding of data, but also a better usage of data in a timely fashion. Data mining, or knowledge discovery from databases, is proposed to gain insight into aspects ofdata and to help peoplemakeinformed,sensible,and better decisions. At present, growing attention has been paid to the study, development, and application of data mining. As a result there is an urgent need for sophisticated techniques and toolsthat can handle new ?elds of data mining, e. g. , spatialdata mining, biomedical data mining, and mining on high-speed and time-variant data streams. The knowledge of data mining should also be expanded to new applications. The 6th International Conference on Advanced Data Mining and Appli- tions(ADMA2010)aimedtobringtogethertheexpertsondataminingthrou- out the world. It provided a leading international forum for the dissemination of original research results in advanced data mining techniques, applications, al- rithms, software and systems, and di?erent applied disciplines. The conference attracted 361 online submissions from 34 di?erent countries and areas. All full papers were peer reviewed by at least three members of the Program Comm- tee composed of international experts in data mining ?elds. A total number of 118 papers were accepted for the conference. Amongst them, 63 papers were selected as regular papers and 55 papers were selected as short papers.
Bibliographic Level Mode of Issuance: Monograph
Includes bibliographical references and index.
III Data Mining Methodologies and Processes -- Incremental Learning by Heterogeneous Bagging Ensemble -- CPLDP: An Efficient Large Dataset Processing System Built on Cloud Platform -- A General Multi-relational Classification Approach Using Feature Generation and Selection -- A Unified Approach to the Extraction of Rules from Artificial Neural Networks and Support Vector Machines -- A Clustering-Based Data Reduction for Very Large Spatio-Temporal Datasets -- Change a Sequence into a Fuzzy Number -- Multiple Kernel Learning Improved by MMD -- A Refinement Approach to Handling Model Misfit in Semi-supervised Learning -- Soft Set Approach for Selecting Decision Attribute in Data Clustering -- Comparison of BEKK GARCH and DCC GARCH Models: An Empirical Study -- Adapt the mRMR Criterion for Unsupervised Feature Selection -- Evaluating the Distance between Two Uncertain Categorical Objects -- Construction Cosine Radial Basic Function Neural Networks Based on Artificial Immune Networks -- Spatial Filter Selection with LASSO for EEG Classification -- Boolean Algebra and Compression Technique for Association Rule Mining -- Cluster Based Symbolic Representation and Feature Selection for Text Classification -- SimRate: Improve Collaborative Recommendation Based on Rating Graph for Sparsity -- Logistic Regression for Transductive Transfer Learning from Multiple Sources -- Double Table Switch: An Efficient Partitioning Algorithm for Bottom-Up Computation of Data Cubes -- IV Data Mining Applications and Systems -- Tag Recommendation Based on Bayesian Principle -- Comparison of Different Methods to Fuse Theos Images -- Using Genetic K-Means Algorithm for PCA Regression Data in Customer Churn Prediction -- Time-Constrained Test Selection for Regression Testing -- Chinese New Word Detection from Query Logs -- Exploiting Concept Clumping for Efficient Incremental E-Mail Categorization -- Topic-Based User Segmentation for Online Advertising with Latent Dirichlet Allocation -- Applying Multi-objective Evolutionary Algorithms to QoS-Aware Web Service Composition -- Real-Time Hand Detection and Tracking Using LBP Features -- Modeling DNS Activities Based on Probabilistic Latent Semantic Analysis -- A New Statistical Approach to DNS Traffic Anomaly Detection -- Managing Power Conservation in Wireless Networks -- Using PCA to Predict Customer Churn in Telecommunication Dataset -- Hierarchical Classification with Dynamic-Threshold SVM Ensemble for Gene Function Prediction -- Personalized Tag Recommendation Based on User Preference and Content -- Predicting Defect Priority Based on Neural Networks -- Personalized Context-Aware QoS Prediction for Web Services Based on Collaborative Filtering -- Hybrid Semantic Analysis System – ATIS Data Evaluation -- Click Prediction for Product Search on C2C Web Sites -- Finding Potential Research Collaborators in Four Degrees of Separation -- Predicting Product Duration for Adaptive Advertisement -- An Algorithm for Available Bandwidth Estimation of IPv6 Network -- A Structure-Based XML Storage Method in YAFFS File System -- A Multi-dimensional Trustworthy Behavior Monitoring Method Based on Discriminant Locality Preserving Projections -- NN-SA Based Dynamic Failure Detector for Services Composition in Distributed Environment -- Two-Fold Spatiotemporal Regression Modeling in Wireless Sensor Networks -- Generating Tags for Service Reviews -- Developing Treatment Plan Support in Outpatient Health Care Delivery with Decision Trees Technique -- Factor Analysis of E-business in Skill-Based Strategic Collaboration -- Increasing the Meaningful Use of Electronic Medical Records: A Localized Health Level 7 Clinical Document Architecture System -- Corpus-Based Analysis of the Co-occurrence of Chinese Antonym Pairs -- Application of Decision-Tree Based on Prediction Model for Project Management -- Management Policies Analysis for Multi-core Shared Caches -- Multi-core Architecture Cache Performance Analysis and Optimization Based on Distributed Method -- The Research on the User Experience of E-Commercial Website Based on User Subdivision -- An Ontology-Based Framework Model for Trustworthy Software Evolution -- Multi-level Log-Based Relevance Feedback Scheme for Image Retrieval -- A Distributed Node Clustering Mechanism in P2P Networks -- Exploratory Factor Analysis Approach for Understanding Consumer Behavior toward Using Chongqing City Card.
With the ever-growing power of generating, transmitting, and collecting huge amounts of data, information overloadis nowan imminent problemto mankind. The overwhelming demand for information processing is not just about a better understanding of data, but also a better usage of data in a timely fashion. Data mining, or knowledge discovery from databases, is proposed to gain insight into aspects ofdata and to help peoplemakeinformed,sensible,and better decisions. At present, growing attention has been paid to the study, development, and application of data mining. As a result there is an urgent need for sophisticated techniques and toolsthat can handle new ?elds of data mining, e. g. , spatialdata mining, biomedical data mining, and mining on high-speed and time-variant data streams. The knowledge of data mining should also be expanded to new applications. The 6th International Conference on Advanced Data Mining and Appli- tions(ADMA2010)aimedtobringtogethertheexpertsondataminingthrou- out the world. It provided a leading international forum for the dissemination of original research results in advanced data mining techniques, applications, al- rithms, software and systems, and di?erent applied disciplines. The conference attracted 361 online submissions from 34 di?erent countries and areas. All full papers were peer reviewed by at least three members of the Program Comm- tee composed of international experts in data mining ?elds. A total number of 118 papers were accepted for the conference. Amongst them, 63 papers were selected as regular papers and 55 papers were selected as short papers.
Artificial intelligence.
Application software.
Information storage and retrieval.
Database management.
Data mining.
Computer communication systems.
Artificial Intelligence.
Information Systems Applications (incl. Internet).
Information Storage and Retrieval.
Database Management.
Data Mining and Knowledge Discovery.
Computer Communication Networks.

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