Advanced Data Mining and Applications
Springer Berlin (Verlag)
978-3-642-17312-7 (ISBN)
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 Exp
| Erscheint lt. Verlag | 5.11.2010 |
|---|---|
| Reihe/Serie | Lecture Notes in Artificial Intelligence | Lecture Notes in Computer Science |
| Zusatzinfo | XIII, 576 p. 198 illus. |
| Verlagsort | Berlin |
| Sprache | englisch |
| Themenwelt | Informatik ► Theorie / Studium ► Künstliche Intelligenz / Robotik |
| Schlagworte | Adaptive Algorithms • bootstrap aggregating • classification • Clustering • Collaborative Filtering • Data Mining • Data Types • Graphs • HPC • Knowledge Discovery • machine learning • Online Communities • pattern mining • Sensor Data • sequences • Social Networks • spatial datasets • temporal datasets • Text Mining • Visualization • Web mining |
| ISBN-10 | 3-642-17312-8 / 3642173128 |
| ISBN-13 | 978-3-642-17312-7 / 9783642173127 |
| Zustand | Neuware |
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