16. PKDD / 23. ECML 2012: Bristol, UK

Privacy and Security

• Ruilin Liu, Wendy Hui Wang, Anna Monreale, Dino Pedreschi, Fosca Giannotti, Wenge Guo:
  AUDIO: An Integrity Auditing Framework of Outlier-Mining-as-a-Service Systems. 1-18
  
• Staal A. Vinterbo:
  Differentially Private Projected Histograms: Construction and Use for Prediction. 19-34
  
• Toshihiro Kamishima, Shotaro Akaho, Hideki Asoh, Jun Sakuma:
  Fairness-Aware Classifier with Prejudice Remover Regularizer. 35-50
  

Rankings and Recommendations

• Evan Kirshenbaum, George Forman, Michael Dugan:
  A Live Comparison of Methods for Personalized Article Recommendation at Forbes.com. 51-66
  
• Balázs Hidasi, Domonkos Tikk:
  Fast ALS-Based Tensor Factorization for Context-Aware Recommendation from Implicit Feedback. 67-82
  
• Weiwei Cheng, Eyke Hüllermeier:
  Probability Estimation for Multi-class Classification Based on Label Ranking. 83-98
  

Reinforcement Learning and Planning

• N. Kemal Ure, Alborz Geramifard, Girish Chowdhary, Jonathan P. How:
  Adaptive Planning for Markov Decision Processes with Uncertain Transition Models via Incremental Feature Dependency Discovery. 99-115
  
• Riad Akrour, Marc Schoenauer, Michèle Sebag:
  APRIL: Active Preference Learning-Based Reinforcement Learning. 116-131
  
• Markus Peters, Wolfgang Ketter, Maytal Saar-Tsechansky, John Collins:
  Autonomous Data-Driven Decision-Making in Smart Electricity Markets. 132-147
  
• Bernard Michini, Jonathan P. How:
  Bayesian Nonparametric Inverse Reinforcement Learning. 148-163
  
• Truong-Huy Dinh Nguyen, Wee Sun Lee, Tze-Yun Leong:
  Bootstrapping Monte Carlo Tree Search with an Imperfect Heuristic. 164-179
  
• Gabriel Dulac-Arnold, Ludovic Denoyer, Philippe Preux, Patrick Gallinari:
  Fast Reinforcement Learning with Large Action Sets Using Error-Correcting Output Codes for MDP Factorization. 180-194
  
• Stefano Ermon, Yexiang Xue, Carla P. Gomes, Bart Selman:
  Learning Policies for Battery Usage Optimization in Electric Vehicles. 195-210
  
• Vivek Ramavajjala, Charles Elkan:
  Policy Iteration Based on a Learned Transition Model. 211-226
  
• Abdeslam Boularias, Oliver Krömer, Jan Peters:
  Structured Apprenticeship Learning. 227-242
  

Rule Mining and Subgroup Discovery

• Dominique Gay, Marc Boullé:
  A Bayesian Approach for Classification Rule Mining in Quantitative Databases. 243-259
  
• Iyad Batal, Gregory F. Cooper, Milos Hauskrecht:
  A Bayesian Scoring Technique for Mining Predictive and Non-Spurious Rules. 260-276
  
• Florian Lemmerich, Martin Becker, Martin Atzmueller:
  Generic Pattern Trees for Exhaustive Exceptional Model Mining. 277-292
  

Semi-Supervised and Transductive Learning

• Tomoharu Iwata, Kevin Duh:
  Bidirectional Semi-supervised Learning with Graphs. 293-306
  
• Saurabh Verma, Estevam R. Hruschka Jr.:
  Coupled Bayesian Sets Algorithm for Semi-supervised Learning and Information Extraction. 307-322
  
• Matan Orbach, Koby Crammer:
  Graph-Based Transduction with Confidence. 323-338
  
• Deguang Kong, Chris H. Q. Ding:
  Maximum Consistency Preferential Random Walks. 339-354
  
• Yuhong Guo, Dale Schuurmans:
  Semi-supervised Multi-label Classification - A Simultaneous Large-Margin, Subspace Learning Approach. 355-370
  

Sensor Data

• Ugo Vespier, Arno J. Knobbe, Siegfried Nijssen, Joaquin Vanschoren:
  MDL-Based Analysis of Time Series at Multiple Time-Scales. 371-386
  
• Sangkyun Lee, Marco Stolpe, Katharina Morik:
  Separable Approximate Optimization of Support Vector Machines for Distributed Sensing. 387-402
  
• Melih Kandemir, Arto Klami, Akos Vetek, Samuel Kaski:
  Unsupervised Inference of Auditory Attention from Biosensors. 403-418
  

Sequence and String Mining

• Sam Blasiak, Huzefa Rangwala, Kathryn B. Laskey:
  A Family of Feed-Forward Models for Protein Sequence Classification. 419-434
  
• Tomohiro I, Yuki Enokuma, Hideo Bannai, Masayuki Takeda:
  General Algorithms for Mining Closed Flexible Patterns under Various Equivalence Relations. 435-450
  
• Jefrey Lijffijt, Panagiotis Papapetrou, Kai Puolamäki:
  Size Matters: Finding the Most Informative Set of Window Lengths. 451-466
  

Social Network Mining

• Francesco Buccafurri, Gianluca Lax, Antonino Nocera, Domenico Ursino:
  Discovering Links among Social Networks. 467-482
  
• Mehdi Kargar, Aijun An, Morteza ZiHayat:
  Efficient Bi-objective Team Formation in Social Networks. 483-498
  
• Liaoruo Wang, Stefano Ermon, John E. Hopcroft:
  Feature-Enhanced Probabilistic Models for Diffusion Network Inference. 499-514
  
• Huy Nguyen, Rong Zheng:
  Influence Spread in Large-Scale Social Networks - A Belief Propagation Approach. 515-530
  
• Konstantinos Pelechrinis, Prashant Krishnamurthy:
  Location Affiliation Networks: Bonding Social and Spatial Information. 531-547
  
• Yu Yang, Enhong Chen, Qi Liu, Biao Xiang, Tong Xu, Shafqat Ali Shad:
  On Approximation of Real-World Influence Spread. 548-564
  
• Masahiro Kimura, Kazumi Saito, Kouzou Ohara, Hiroshi Motoda:
  Opinion Formation by Voter Model with Temporal Decay Dynamics. 565-580
  
• Ramasuri Narayanam, Amit Anil Nanavati:
  Viral Marketing for Product Cross-Sell through Social Networks. 581-596
  
• Deqing Yang, Yanghua Xiao, Bo Xu, Hanghang Tong, Wei Wang, Sheng Huang:
  Which Topic Will You Follow? 597-612
  

Spatial and Geographical Data Mining

• Honglei Zhuang, Alvin Chin, Sen Wu, Wei Wang, Xia Wang, Jie Tang:
  Inferring Geographic Coincidence in Ephemeral Social Networks. 613-628
  
• Thomas Liebig, Zhao Xu, Michael May, Stefan Wrobel:
  Pedestrian Quantity Estimation with Trajectory Patterns. 629-643
  
• Jun-Ming Xu, Aniruddha Bhargava, Robert Nowak, Xiaojin Zhu:
  Socioscope: Spatio-temporal Signal Recovery from Social Media. 644-659
  

Statistical Methods and Evaluation

• Gaurav Misra, Behzad Golshan, Evimaria Terzi:
  A Framework for Evaluating the Smoothness of Data-Mining Results. 660-675
  
• Christoph Sawade, Steffen Bickel, Timo von Oertzen, Tobias Scheffer, Niels Landwehr:
  Active Evaluation of Ranking Functions Based on Graded Relevance. 676-691
  

Time Series and Temporal Data Mining

• Manish Gupta, Jing Gao, Yizhou Sun, Jiawei Han:
  Community Trend Outlier Detection Using Soft Temporal Pattern Mining. 692-708
  
• Caio Dias Valentim, Eduardo Sany Laber, David Sotelo:
  Data Structures for Detecting Rare Variations in Time Series. 709-724
  
• Josif Grabocka, Alexandros Nanopoulos, Lars Schmidt-Thieme:
  Invariant Time-Series Classification. 725-740
  
• Tzu-Kuo Huang, Jeff G. Schneider:
  Learning Bi-clustered Vector Autoregressive Models. 741-756
  

Transfer Learning

• Fangwei Hu, Tianqi Chen, Nathan Nan Liu, Qiang Yang, Yong Yu:
  Discriminative Factor Alignment across Heterogeneous Feature Space. 757-772
  
• Nan Li, William W. Cohen, Kenneth R. Koedinger:
  Learning to Perceive Two-Dimensional Displays Using Probabilistic Grammars. 773-788
  
• Wenhao Jiang, Fu-Lai Chung:
  Transfer Spectral Clustering. 789-803
  

System Demonstrations Track

• Mus'ab Husaini, Ahmet Koçyigit, Dilek Tapucu, Berrin A. Yanikoglu, Yücel Saygin:
  An Aspect-Lexicon Creation and Evaluation Tool for Sentiment Analysis Researchers. 804-807
  
• Radek Skrabal, Milan Simunek, Stanislav Vojír, Andrej Hazucha, Tomás Marek, David Chudán, Tomás Kliegr:
  Association Rule Mining Following the Web Search Paradigm. 808-811
  
• Andreas Niekler, Patrick Jähnichen, Gerhard Heyer:
  ASV Monitor: Creating Comparability of Machine Learning Methods for Content Analysis. 812-815
  
• Janez Kranjc, Vid Podpecan, Nada Lavrac:
  ClowdFlows: A Cloud Based Scientific Workflow Platform. 816-819
  
• Phan Nhat Hai, Dino Ienco, Pascal Poncelet, Maguelonne Teisseire:
  Extracting Trajectories through an Efficient and Unifying Spatio-temporal Pattern Mining System. 820-823
  
• Gabriel Kronberger, Stefan Wagner, Michael Kommenda, Andreas Beham, Andreas Scheibenpflug, Michael Affenzeller:
  Knowledge Discovery through Symbolic Regression with HeuristicLab. 824-827
  
• Emmanuel Müller, Fabian Keller, Sebastian Blanc, Klemens Böhm:
  OutRules: A Framework for Outlier Descriptions in Multiple Context Spaces. 828-832
  
• Peter Reutemann, Joaquin Vanschoren:
  Scientific Workflow Management with ADAMS. 833-837
  
• Alexander Hinneburg, Rico Preiss, René Schröder:
  TopicExplorer: Exploring Document Collections with Topic Models. 838-841
  
• Martin Atzmueller, Florian Lemmerich:
  VIKAMINE - Open-Source Subgroup Discovery, Pattern Mining, and Analytics. 842-845
  

Nectar Track

• Maria-Florina Balcan, Nicholas J. A. Harvey:
  Learning Submodular Functions. 846-849
  
• Kristian Kersting, Christian Bauckhage, Christian Thurau, Mirwaes Wahabzada:
  Matrix Factorization as Search. 850-853
  
• Marco Lippi, Andrea Passerini, Marco Punta, Paolo Frasconi:
  Metal Binding in Proteins: Machine Learning Complements X-Ray Absorption Spectroscopy. 854-857
  
• Andrew Gordon Wilson, Zoubin Ghahramani:
  Modelling Input Varying Correlations between Multiple Responses. 858-861
  

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