Advances in Knowledge Discovery and Data Mining

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The two-volume set LNAI 7818 + LNAI 7819 constitutes the refereed proceedings of the 17th Pacific-Asia Conference on Knowledge Dis...

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Beschreibung

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.
State-of-the-art research Fast track conference proceedings Up-to-date results in knowledge discovery and data mining
Inhalt
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.