By: Pang-Ning Tan (Editor), Sanjay Chawla (Editor), Chin Kuan Ho (Editor), James Bailey (Editor)

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The two-volume set "LNAI" 7301 and 7302 constitutes the refereed proceedings of the 16th Pacific-Asia Conference on Knowledge Discovery and Data Mining, PAKDD 2012, held in Kuala Lumpur, Malaysia, in May 2012. The total of 20 revised full papers and 66 revised short papers were carefully reviewed and selected from 241 submissions. The papers present new ideas, original research results, and practical development experiences from all KDD-related areas. The papers are organized in topical sections on supervised learning: active, ensemble, rare-class and online; unsupervised learning: clustering, probabilistic modeling in the first volume and on pattern mining: networks, graphs, time-series and outlier detection, and data manipulation: pre-processing and dimension reduction in the second volume.

Supervised Learning: Active, Ensemble, Rare-Class and Online
Time-Evolving Relational Classification and Ensemble Methods	p. 1
Active Learning for Hierarchical Text Classification	p. 14
TeamSkill Evolved: Mixed Classification Schemes for Team-Based Multi-player Games	p. 26
A Novel Weighted Ensemble Technique for Time Series Forecasting	p. 38
Techniques for Efficient Learning without Search	p. 50
An Aggressive Margin-Based Algorithm for Incremental Learning	p. 62
Two-View Online Learning	p. 74
A Generic Classifier-Ensemble Approach for Biomedical Named Entity Recognition	p. 86
Neighborhood Random Classification	p. 98
SRF: A Framework for the Study of Classifier Behavior under Training Set Mislabeling Noise	p. 109
Building Decision Trees for the Multi-class Imbalance Problem	p. 122
Scalable Random Forests for Massive Data	p. 135
Hybrid Random Forests: Advantages of Mixed Trees in Classifying Text Data	p. 147
Learning Tree Structure of Label Dependency for Multi-label Learning	p. 159
Multiple Instance Learning for Group Record Linkage	p. 171
Incremental Set Recommendation Based on Class Differences	p. 183
Active Learning for Cross Language Text Categorization	p. 195
Evasion Attack of Multi-class Linear Classifiers	p. 207
Foundation of Mining Class-Imbalanced Data	p. 219
Active Learning with c-Certainty	p. 231
A Term Association Translation Model for Naive Bayes Text Classification	p. 243
A Double-Ensemble Approach for Classifying Skewed Data Streams	p. 254
Generating Balanced Classifier-Independent Training Samples from Unlabeled Data	p. 266
Nyström Approximate Model Selection for LSSVM	p. 282
Exploiting Label Dependency for Hierarchical Multi-label Classification	p. 294
Diversity Analysis on Boosting Nominal Concepts	p. 306
Extreme Value Prediction for Zero-Inflated Data	p. 318
Learning to Diversify Expert Finding with Subtopics	p. 330
An Associative Classifier for Uncertain Datasets	p. 342
Unsupervised Learning: Clustering, Probabilistic Modeling
Neighborhood-Based Smoothing of External Cluster Validity Measures	p. 354
Sequential Entity Group Topic Model for Getting Topic Flows of Entity Groups within One Document	p. 366
Topological Comparisons of Proximity Measures	p. 379
Quad-tuple PLSA: Incorporating Entity and Its Rating in Aspect Identification	p. 392
Clustering-Based ¿-Anonymity	p. 405
Unsupervised Ensemble Learning for Mining Top-n Outliers	p. 418
Towards Personalized Context-Aware Recommendation by Mining Context Logs through Topic Models	p. 431
Mining of Temporal Coherent Subspace Clusters in Multivariate Time Series Databases	p. 444
A Vertex Similarity Probability Model for Finding Network Community Structure	p. 456
Hybrid-¿-greedy for Mobile Context-Aware Recommender System	p. 468
Unsupervised Multi-label Text Classification Using a World Knowledge Ontology	p. 480
Semantic Social Network Analysis with Text Corpora	p. 493
Visualizing Clusters in Parallel Coordinates for Visual Knowledge Discovery	p. 505
Feature Enriched Nonparametric Bayesian Co-clustering	p. 517
Shape-Based Clustering for Time Series Data	p. 530
Privacy-Preserving EM Algorithm for Clustering on Social Network	p. 542
Named Entity Recognition and Identification for Finding the Owner of a Home Page	p. 554
Clustering and Understanding Documents via Discrimination Information Maximization	p. 566
A Semi-supervised Incremental Clustering Algorithm for Streaming Data	p. 578
Unsupervised Sparse Matrix Co-clustering for Marketing and Sales Intelligence	p. 591
Expectation-Maximization Collaborative Filtering with Explicit and Implicit Feedback	p. 604
Author Index	p. 617
Table of Contents provided by Ingram. All Rights Reserved.

ISBN: 9783642302169
ISBN-10: 3642302165
Series: Lecture Notes in Computer Science / Lecture Notes in Artificial Intelligence
Audience: Professional
Format: Paperback
Language: English
Number Of Pages: 642
Published: 25th May 2012
Dimensions (cm): 23.5 x 15.5  x 3.3
Weight (kg): 0.93