Advances in knowledge discovery and data mining : 17th Pacific-Asia Conference, PAKDD 2013, Gold Coast, Australia, April 14-17, 2013 : proceedings
著者
書誌事項
Advances in knowledge discovery and data mining : 17th Pacific-Asia Conference, PAKDD 2013, Gold Coast, Australia, April 14-17, 2013 : proceedings
（Lecture notes in computer science, 7818-7819 . Lecture notes in artificial intelligence）
Springer, c2013
- pt. 1
- pt. 2
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注記
Includes bibliographical references and index
内容説明・目次
- 巻冊次
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pt. 1 ISBN 9783642374524
内容説明
The two-volume set LNAI 7818 + LNAI 7819 constitutes the refereed proceedings of the 17th Pacific-Asia Conference on Knowledge Discovery and Data Mining, PAKDD 2013, held in Gold Coast, Australia, in April 2013.
The total of 98 papers presented in these proceedings was carefully reviewed and selected from 363 submissions. They cover the general fields of data mining and KDD extensively, including pattern mining, classification, graph mining, applications, machine learning, feature selection and dimensionality reduction, multiple information sources mining, social networks, clustering, text mining, text classification, imbalanced data, privacy-preserving data mining, recommendation, multimedia data mining, stream data mining, data preprocessing and representation.
目次
Discovering Local Subgroups, with an Application to Fraud Detection.- PUF-Tree: A Compact Tree Structure for Frequent Pattern Mining of Uncertain Data.- Frequent Pattern Mining in Attributed Trees.- Mining Frequent Patterns from Human Interactions in Meetings Using Directed Acyclic Graphs.- ClaSP: An Efficient Algorithm for Mining Frequent Closed Sequences.- Efficient Mining of Contrast Patterns on Large Scale Imbalanced Real-Life Data.- Online Cross-Lingual PLSI for Evolutionary Theme Patterns Analysis.- F-Trail: Finding Patterns in Taxi Trajectories.- Mining Appliance Usage Patterns in Smart Home Environment.- Computational Models of Stress in Reading Using Physiological and Physical Sensor Data.- Latent Patient Profile Modelling and Applications with Mixed-Variate Restricted Boltzmann Machine.- MassBayes: A New Generative Classifier with Multi-dimensional Likelihood Estimation.- Fast and Effective Single Pass Bayesian Learning.- Sparse Reductions for Fixed-Size Least Squares Support Vector Machines on Large Scale Data.- Discovery of Regional Co-location Patterns with k-Nearest Neighbor Graph.- Spectral Decomposition for Optimal Graph Index Prediction.- Patterns amongst Competing Task Frequencies: Super-Linearities, and the Almond-DG Model.- Node Classification in Social Network via a Factor Graph Model.- Fast Graph Stream Classification Using Discriminative Clique Hashing.- Mining Interesting Itemsets in Graph Datasets.- Robust Synchronization-Based Graph Clustering.- Efficient Mining of Combined Subspace and Subgraph Clusters in Graphs with Feature Vectors.- Exploiting Temporal Information in a Two-Stage Classification Framework for Content-Based Depression Detection.- EEG-Based Person Verification Using Multi-Sphere SVDD and UBM.- Measuring Reproducibility of High-Throughput Deep-Sequencing Experiments Based on Self-adaptive Mixture Copula.- Mining Representative Movement Patterns through Compression.- NARGES: Prediction Model for Informed Routing in a Communications Network.- Mining Usage Traces of Mobile Apps for Dynamic Preference Prediction.- Leveraging Hybrid Citation Context for Impact Summarization.- Optimal Allocation of High Dimensional Assets through Canonical Vines.- Inducing Context Gazetteers from Encyclopedic Databases for Named Entity Recognition.- An Optimization Method for Proportionally Diversifying Search Results.- Joint Naive Bayes and LDA for Unsupervised Sentiment Analysis.- An Unsupervised Learning Model to Perform Side Channel Attack.- Decisive Supervised Learning.- Learning Overlap Optimization for Domain Decomposition Methods.- CLUEKR : CLUstering Based Efficient kNN Regression.- AREM: A Novel Associative Regression Model Based on EM Algorithm.- One-Class Transfer Learning with Uncertain Data.- Time Series Forecasting Using Distribution Enhanced Linear Regression.- Twin Bridge Transfer Learning for Sparse Collaborative Filtering.- Dimensionality Reduction with Dimension Selection.- Multi-View Visual Classification via a Mixed-Norm Regularizer.- Mining Specific Features for Acquiring User Information Needs.- Ensemble-Based Wrapper Methods for Feature Selection and Class Imbalance Learning.- Exploring Groups from Heterogeneous Data via Sparse Learning.- Multiplex Topic Models.- Integrating Clustering and Ranking on Hybrid Heterogeneous Information Network.- Learning from Multiple Observers with Unknown Expertise.
- 巻冊次
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pt. 2 ISBN 9783642374555
内容説明
The two-volume set LNAI 7818 + LNAI 7819 constitutes the refereed proceedings of the 17th Pacific-Asia Conference on Knowledge Discovery and Data Mining, PAKDD 2013, held in Gold Coast, Australia, in April 2013.
The total of 98 papers presented in these proceedings was carefully reviewed and selected from 363 submissions. They cover the general fields of data mining and KDD extensively, including pattern mining, classification, graph mining, applications, machine learning, feature selection and dimensionality reduction, multiple information sources mining, social networks, clustering, text mining, text classification, imbalanced data, privacy-preserving data mining, recommendation, multimedia data mining, stream data mining, data preprocessing and representation.
目次
ProCF: Probabilistic Collaborative Filtering for Reciprocal Recommendation.- Product and User Dependent Social Network Models for Recommender Systems.- Learning Representative Nodes in Social Networks.- Tracing Influential Nodes in a Social Network with Competing
Information.- ViStruclizer: A Structural Visualizer for Multi-dimensional Social Networks.- Influential Nodes in a One-Wave Diffusion Model for Location-Based Social Networks.- Modeling Social Information Learning among Taxi Drivers.- Mining User Interests from Information Sharing Behaviors in Social Media.- Anonymization for Multiple Released Social Network Graphs.- A New, Fast and Accurate Algorithm for Hierarchical Clustering on Euclidean Distances.- Clustering Patient Medical Records via Sparse Subspace Representation.- A Unified Metric for Categorical and Numerical Attributes in Data Clustering.- An Extension of the Infinite Relational Model Incorporating Interaction between Objects.- Density-Based Clustering Based on Hierarchical Density Estimates.- Stock Trend Prediction by Classifying Aggregative Web Topic-Opinion.- The Role of Hubs in Cross-Lingual Supervised Document Retrieval.- Text Document Topical Recursive Clustering and Automatic Labeling of a Hierarchy of Document Clusters.- Query-Document Relevance Topic Models.- A Two-Stage Approach for Generating Topic Models.- Effective Top-Down Active Learning for Hierarchical Text Classification.- Forgetting Word Segmentation in Chinese Text Classification with L1-Regularized Logistic Regression.- Crest: Cluster-based Representation Enrichment for Short Text Classification.- Cross Language Prediction of Vandalism on Wikipedia Using Article Views and Revisions.- An Optimized Cost-Sensitive SVM for Imbalanced Data Learning.- A Positive-biased Nearest Neighbour Algorithm for Imbalanced Classification.- Class Based Weighted K-Nearest Neighbor over Imbalance Dataset.- ProWSyn: Proximity Weighted Synthetic Oversampling Technique for Imbalanced Data Set Learning.- Differential Privacy Preserving Spectral Graph Analysis.- Sorted Nearest Neighborhood Clustering for Efficient Private Blocking.- On Linear Refinement of Differential Privacy-Preserving Query Answering.- A Coupled Clustering Approach for Items Recommendation.- Location Recommendation Based on Periodicity of Human Activities and Location Categories.- Top-N Recommendations by Learning User Preference Dynamics.- Semantic Title Evaluation and Recommendation Based on Topic Models.- Video Quality Prediction over Wireless 4G.- A Self-immunizing Manifold Ranking for Image Retrieval.- Low-Rank Matrix Recovery with Discriminant Regularization.- Multi-Manifold Ranking: Using Multiple Features for Better Image
Retrieval.- One Pass Concept Change Detection for Data Streams.- Incremental Mining of Significant URLs in Real-Time and Large-Scale
Social Streams.- A Concept-Drifting Detection Algorithm for Categorical Evolving Data.- Framework for Storing and Processing Relational Entities in Stream Mining.- Discovering Semantics from Multiple Correlated Time Series Stream.- Matrix Factorization With Aggregated Observations.- An Approach to Identifying False Traces in Process Event Logs.- Split-Merge Augmented Gibbs Sampling for Hierarchical Dirichlet Processes.- Adaptive Temporal Entity Resolution on Dynamic Databases.- Fuzzy Multi-Sphere Support Vector Data Description.
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