Advances in Knowledge Discovery and Data Mining, Part II 14th Pacific-Asia Conference, PAKDD 2010, Hyderabad, India, June 21-24, 2010, Proceedings /
Clasificación: | Libro Electrónico |
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Autor Corporativo: | |
Otros Autores: | , , , |
Formato: | Electrónico eBook |
Idioma: | Inglés |
Publicado: |
Berlin, Heidelberg :
Springer Berlin Heidelberg : Imprint: Springer,
2010.
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Edición: | 1st ed. 2010. |
Colección: | Lecture Notes in Artificial Intelligence,
6119 |
Temas: | |
Acceso en línea: | Texto Completo |
Tabla de Contenidos:
- Session 4B. Dimensionality Reduction/Parallelism
- Subclass-Oriented Dimension Reduction with Constraint Transformation and Manifold Regularization
- Distributed Knowledge Discovery with Non Linear Dimensionality Reduction
- DPSP: Distributed Progressive Sequential Pattern Mining on the Cloud
- An Approach for Fast Hierarchical Agglomerative Clustering Using Graphics Processors with CUDA
- Session 5A. Novel Applications
- Ontology-Based Mining of Brainwaves: A Sequence Similarity Technique for Mapping Alternative Features in Event-Related Potentials (ERP) Data
- Combining Support Vector Machines and the t-statistic for Gene Selection in DNA Microarray Data Analysis
- Satrap: Data and Network Heterogeneity Aware P2P Data-Mining
- Player Performance Prediction in Massively Multiplayer Online Role-Playing Games (MMORPGs)
- Relevant Gene Selection Using Normalized Cut Clustering with Maximal Compression Similarity Measure
- Session 5B. Feature Selection/Visualization
- A Novel Prototype Reduction Method for the K-Nearest Neighbor Algorithm with K???1
- Generalized Two-Dimensional FLD Method for Feature Extraction: An Application to Face Recognition
- Learning Gradients with Gaussian Processes
- Analyzing the Role of Dimension Arrangement for Data Visualization in Radviz
- Session 6A. Graph Mining
- Subgraph Mining on Directed and Weighted Graphs
- Finding Itemset-Sharing Patterns in a Large Itemset-Associated Graph
- A Framework for SQL-Based Mining of Large Graphs on Relational Databases
- Fast Discovery of Reliable k-terminal Subgraphs
- GTRACE2: Improving Performance Using Labeled Union Graphs
- Session 6B. Clustering II
- Orthogonal Nonnegative Matrix Tri-factorization for Semi-supervised Document Co-clustering
- Rule Synthesizing from Multiple Related Databases
- Fast Orthogonal Nonnegative Matrix Tri-Factorization for Simultaneous Clustering
- Hierarchical Web-Page Clustering via In-Page and Cross-Page Link Structures
- Mining Numbers in Text Using Suffix Arrays and Clustering Based on Dirichlet Process Mixture Models
- Session 7A. Opinion/Sentiment Mining
- Opinion-Based Imprecise Query Answering
- Blog Opinion Retrieval Based on Topic-Opinion Mixture Model
- Feature Subsumption for Sentiment Classification in Multiple Languages
- Decentralisation of ScoreFinder: A Framework for Credibility Management on User-Generated Contents
- Classification and Pattern Discovery of Mood in Weblogs
- Capture of Evidence for Summarization: An Application of Enhanced Subjective Logic
- Session 7B. Stream Mining
- Fast Perceptron Decision Tree Learning from Evolving Data Streams
- Classification and Novel Class Detection in Data Streams with Active Mining
- Bulk Loading Hierarchical Mixture Models for Efficient Stream Classification
- Summarizing Multidimensional Data Streams: A Hierarchy-Graph-Based Approach
- Efficient Trade-Off between Speed Processing and Accuracy in Summarizing Data Streams
- Subsequence Matching of Stream Synopses under the Time Warping Distance
- Session 8A. Similarity and Kernels
- Normalized Kernels as Similarity Indices
- Adaptive Matching Based Kernels for Labelled Graphs
- A New Framework for Dissimilarity and Similarity Learning
- Semantic-Distance Based Clustering for XML Keyword Search
- Session 8B. Graph Analysis
- oddball: Spotting Anomalies in Weighted Graphs
- Robust Outlier Detection Using Commute Time and Eigenspace Embedding
- EigenSpokes: Surprising Patterns and Scalable Community Chipping in Large Graphs
- BASSET: Scalable Gateway Finder in Large Graphs
- Session 8C. Classification II
- Ensemble Learning Based on Multi-Task Class Labels
- Supervised Learning with Minimal Effort
- Generating Diverse Ensembles to Counter the Problem of Class Imbalance
- Relationship between Diversity and Correlation in Multi-Classifier Systems
- Compact Margin Machine.