9. PAKDD 2005: Hanoi, Vietnam

Keynote Speech and Invited Talks

• Tom M. Mitchell:
  Machine Learning for Analyzing Human Brain Function. 1
  
• Nada Lavrac:
  Subgroup Discovery Techniques and Applications. 2-14
  
• Unna Huh:
  IT Development in the 21^st Century and Its Implications. 15-20
  

Theoretic Foundations

• Tran Trang, Nguyen Cam Chi, Hoang Ngoc Minh:
  Data Mining of Gene Expression Microarray via Weighted Prefix Trees. 21-31
  
• Hiroshi Echizen-ya, Kenji Araki, Yoshio Momouchi:
  Automatic Extraction of Low Frequency Bilingual Word Pairs from Parallel Corpora with Various Languages. 32-37
  
• Ling Zhang, Tao Wu, Yanping Zhang:
  A Kernel Function Method in Clustering. 38-42
  
• Nan Zhang, Wei Zhao, Jianer Chen:
  Performance Measurements for Privacy Preserving Data Mining. 43-49
  
• Yoshikazu Shima, Kouichi Hirata, Masateru Harao:
  Extraction of Frequent Few-Overlapped Monotone DNF Formulas with Depth-First Pruning. 50-60
  

Association Rules

• Ying Zhang, Hongye Su, Tao Jia, Jian Chu:
  Rule Extraction from Trained Support Vector Machines. 61-70
  
• Shiying Huang, Geoffrey I. Webb:
  Pruning Derivative Partial Rules During Impact Rule Discovery. 71-80
  
• Ghada Gasmi, Sadok Ben Yahia, Engelbert Mephu Nguifo, Yahya Slimani:
  IGB: A New Informative Generic Base of Association Rules. 81-90
  
• Sadok Ben Yahia, Yahya Slimani, Jihem Rezgui:
  A Divide and Conquer Approach for Deriving Partially Ordered Sub-structures. 91-96
  
• Yun Sing Koh, Nathan Rountree:
  Finding Sporadic Rules Using Apriori-Inverse. 97-106
  
• Manoranjan Dash, Deepak Kolippakkam:
  Automatic View Selection: An Application to Image Mining. 107-113
  
• Francesco Bonchi, Claudio Lucchese:
  Pushing Tougher Constraints in Frequent Pattern Mining. 114-124
  
• Mafruz Zaman Ashrafi, David Taniar, Kate A. Smith:
  An Efficient Compression Technique for Frequent Itemset Generation in Association Rule Mining. 125-135
  
• Jin Soung Yoo, Pusheng Zhang, Shashi Shekhar:
  Mining Time-Profiled Associations: An Extended Abstract. 136-142
  
• K. K. Loo, Ivy Tong, Ben Kao:
  Online Algorithms for Mining Inter-stream Associations from Large Sensor Networks. 143-149
  
• Zhi-Hong Deng, Cong-Rui Ji, Ming Zhang, Shi-Wei Tang:
  Mining Frequent Ordered Patterns. 150-154
  

Biomedical Domains

• Lior Lukov, Sanjay Chawla, W. Bret Church:
  Conditional Random Fields for Transmembrane Helix Prediction. 155-161
  
• Woo-Cheol Kim, Sanghyun Park, Jung-Im Won, Sang-Wook Kim, Jeehee Yoon:
  A DNA Index Structure Using Frequency and Position Information of Genetic Alphabet. 162-172
  
• Min Song, Il-Yeol Song, Xiaohua Hu, Robert B. Allen:
  An Automatic Unsupervised Querying Algorithm for Efficient Information Extraction in Biomedical Domain. 173-179
  
• Thai Quang Tung, Doheon Lee, Dae-Won Kim, Jong-Tae Lim:
  Voting Fuzzy k-NN to Predict Protein Subcellular Localization from Normalized Amino Acid Pair Compositions. 180-185
  
• Richard D. De Veaux, Thu Hoàng:
  Comparison of Tree Based Methods on Mammography Data. 186-191
  
• Michael Mayo:
  Bayesian Sequence Learning for Predicting Protein Cleavage Points. 192-202
  
• Jung-Im Won, Jeehee Yoon, Sanghyun Park, Sang-Wook Kim:
  A Novel Indexing Method for Efficient Sequence Matching in Large DNA Database Environment. 203-215
  

Classification and Ranking

• Frans Coenen, Paul H. Leng, Lu Zhang:
  Threshold Tuning for Improved Classification Association Rule Mining. 216-225
  
• Hoai Bac Le, Nguyen Anh Tuan:
  Using Rough Set in Feature Selection and Reduction in Face Recognition Problem. 226-233
  
• Gerrit K. Janssens, Kenneth Sörensen, Arthur Limère, Koen Vanhoof:
  Analysis of Company Growth Data Using Genetic Algorithms on Binary Trees. 234-239
  
• Rafal Rak, Wojciech Stach, Osmar R. Zaïane, Maria-Luiza Antonie:
  Considering Re-occurring Features in Associative Classifiers. 240-248
  
• Arit Thammano, Asavin Meengen:
  A New Evolutionary Neural Network Classifier. 249-255
  
• Weiping Ge, Wei Wang, Xiaorong Li, Baile Shi:
  A Privacy-Preserving Classification Mining Algorithm. 256-261
  
• Cuong Anh Le, Van-Nam Huynh, Akira Shimazu:
  Combining Classifiers with Multi-representation of Context in Word Sense Disambiguation. 262-268
  
• Kazuko Takahashi, Hiroya Takamura, Manabu Okumura:
  Automatic Occupation Coding with Combination of Machine Learning and Hand-Crafted Rules. 269-279
  
• Hua Huo, Boqin Feng:
  Retrieval Based on Language Model with Relative Entropy and Feedback. 280-289
  
• Cao D. Nguyen, Tran A. Dung, Tru H. Cao:
  Text Classification for DAG-Structured Categories. 290-300
  
• Shotaro Matsumoto, Hiroya Takamura, Manabu Okumura:
  Sentiment Classification Using Word Sub-sequences and Dependency Sub-trees. 301-311
  
• Sinh Hoa Nguyen, Hung Son Nguyen:
  Improving Rough Classifiers Using Concept Ontology. 312-322
  
• Yi-Hong Chu, Kun-Ta Chuang, Ming-Syan Chen:
  QED: An Efficient Framework for Temporal Region Query Processing. 323-332
  

Clustering

• Jessica Lin, Michail Vlachos, Eamonn J. Keogh, Dimitrios Gunopulos, Jian-Wei Liu, Shou-Jian Yu, Jia-Jin Le:
  A MPAA-Based Iterative Clustering Algorithm Augmented by Nearest Neighbors Search for Time-Series Data Streams. 333-342
  
• Zheng Liu, Jeffrey Xu Yu, Xuemin Lin, Hongjun Lu, Wei Wang:
  Locating Motifs in Time-Series Data. 343-353
  
• Satu Elisa Schaeffer:
  Stochastic Local Clustering for Massive Graphs. 354-360
  
• Shuigeng Zhou, Yue Zhao, Jihong Guan, Joshua Zhexue Huang:
  A Neighborhood-Based Clustering Algorithm. 361-371
  
• Jun Liu, Kotagiri Ramamohanarao:
  Improved Self-splitting Competitive Learning Algorithm. 372-377
  
• Mirco Nanni:
  Speeding-Up Hierarchical Agglomerative Clustering in Presence of Expensive Metrics. 378-387
  
• Andy M. Yip, Chris H. Q. Ding, Tony F. Chan:
  Dynamic Cluster Formation Using Level Set Methods. 388-398
  
• Georg Pölzlbauer, Andreas Rauber, Michael Dittenbach:
  A Vector Field Visualization Technique for Self-organizing Maps. 399-409
  
• Denny, David McG. Squire:
  Visualization of Cluster Changes by Comparing Self-organizing Maps. 410-419
  
• Jing Gao, Jianzhong Li, Zhaogong Zhang, Pang-Ning Tan:
  An Incremental Data Stream Clustering Algorithm Based on Dense Units Detection. 420-425
  
• Lydia Boudjeloud, François Poulet:
  Visual Interactive Evolutionary Algorithm for High Dimensional Data Clustering and Outlier Detection. 426-431
  
• Hans-Peter Kriegel, Peter Kunath, Martin Pfeifle, Matthias Renz:
  Approximated Clustering of Distributed High-Dimensional Data. 432-441
  

Dynamic Data Mining

• Son N. Nguyen, Xingzhi Sun, Maria E. Orlowska:
  Improvements of IncSpan: Incremental Mining of Sequential Patterns in Large Database. 442-451
  
• Surong Wang, Manoranjan Dash, Liang-Tien Chia:
  Efficient Sampling: Application to Image Data. 452-463
  
• Qiang Li, Bo Zhang:
  Cluster-Based Rough Set Construction. 464-473
  

Graphic Model Discovery

• Xiao-Lin Li, Xiangdong He, Senmiao Yuan:
  Learning Bayesian Networks Structures from Incomplete Data: An Efficient Approach Based on Extended Evolutionary Programming. 474-479
  
• Sunghwan Min, Ingoo Han:
  Dynamic Fuzzy Clustering for Recommender Systems. 480-485
  
• Fang Chu, Yizhou Wang, Carlo Zaniolo, Douglas Stott Parker Jr.:
  Improving Mining Quality by Exploiting Data Dependency. 486-499
  

High Dimensional Data

• Xiaoyang Tan, Songcan Chen, Zhi-Hua Zhou, Fuyan Zhang:
  Feature Selection for High Dimensional Face Image Using Self-organizing Maps. 500-504
  
• Kun-Ta Chuang, Ming-Syan Chen, Wen-Chieh Yang:
  Progressive Sampling for Association Rules Based on Sampling Error Estimation. 505-515
  
• Kiyoung Yang, Hyunjin Yoon, Cyrus Shahabi:
  CL eVer: A Feature Subset Selection Technique for Multivariate Time Series. 516-522
  
• Hirotaka Niitsuma, Takashi Okada:
  Covariance and PCA for Categorical Variables. 523-528
  

Integration of Data Warehousing

• Tianyi Wu, Jian Xu, Chen Wang, Wei Wang, Baile Shi:
  ADenTS: An Adaptive Density-Based Tree Structure for Approximating Aggregate Queries over Real Attributes. 529-538
  
• Xuequn Shang, Kai-Uwe Sattler:
  Frequent Itemset Mining with Parallel RDBMS. 539-544
  

Knowledge Management

• Ngoc Thanh Nguyen, Michal Malowiecki:
  Using Consensus Susceptibility and Consistency Measures for Inconsistent Knowledge Management. 545-554
  
• Unil Yun, John J. Leggett:
  WLPMiner: Weighted Frequent Pattern Mining with Length-Decreasing Support Constraints. 555-567
  

Machine Learning Methods

• Rong Jin, Yi Liu:
  A Framework for Incorporating Class Priors into Discriminative Classification. 568-577
  
• Chia Huey Ooi, Madhu Chetty:
  Increasing Classification Accuracy by Combining Adaptive Sampling and Convex Pseudo-Data. 578-587
  
• Adam Woznica, Alexandros Kalousis, Melanie Hilario:
  Kernels over Relational Algebra Structures. 588-598
  
• Junping Zhang, Stan Z. Li:
  Adaptive Nonlinear Auto-Associative Modeling Through Manifold Learning. 599-604
  
• Fei Tony Liu, Kai Ming Ting, Wei Fan:
  Maximizing Tree Diversity by Building Complete-Random Decision Trees. 605-610
  
• Ming Li, Zhi-Hua Zhou:
  SETRED: Self-training with Editing. 611-621
  
• Luo Si, Rong Jin:
  Adjusting Mixture Weights of Gaussian Mixture Model via Regularized Probabilistic Latent Semantic Analysis. 622-631
  
• Liefeng Bo, Ling Wang, Licheng Jiao:
  Training Support Vector Machines Using Greedy Stagewise Algorithm. 632-638
  
• Phu Chien Nguyen, Kouzou Ohara, Hiroshi Motoda, Takashi Washio:
  Cl-GBI: A Novel Approach for Extracting Typical Patterns from Graph-Structured Data. 639-649
  
• Raju Shrestha, Yaping Lin:
  Improved Bayesian Spam Filtering Based on Co-weighted Multi-area Information. 650-660
  

Novel Algorithms

• Arnaud Soulet, Bruno Crémilleux:
  An Efficient Framework for Mining Flexible Constraints. 661-671
  
• Marzena Kryszkiewicz, Katarzyna Cichon:
  Support Oriented Discovery of Generalized Disjunction-Free Representation of Frequent Patterns with Negation. 672-682
  
• Wenyin Tang, Kezhi Mao:
  Feature Selection Algorithm for Data with Both Nominal and Continuous Features. 683-688
  
• Ying Liu, Wei-keng Liao, Alok N. Choudhary:
  A Two-Phase Algorithm for Fast Discovery of High Utility Itemsets. 689-695
  
• Marek Wojciechowski, Maciej Zakrzewicz:
  On Multiple Query Optimization in Data Mining. 696-701
  
• Zhuowei Li, Amitabha Das, Jianying Zhou:
  USAID: Unifying Signature-Based and Anomaly-Based Intrusion Detection. 702-712
  

Spatial Data

• San-Yih Hwang, Ying-Han Liu, Jeng-Kuen Chiu, Ee-Peng Lim:
  Mining Mobile Group Patterns: A Trajectory-Based Approach. 713-718
  
• Yan Huang, Liqin Zhang, Ping Yu:
  Can We Apply Projection Based Frequent Pattern Mining Paradigm to Spatial Co-location Mining? 719-725
  
• Yu Qian, Kang Zhang, D. T. Huynh:
  PatZip: Pattern-Preserved Spatial Data Compression. 726-736
  

Temporal Data

• Gareth J. Janacek, Anthony J. Bagnall, M. Powell:
  A Likelihood Ratio Distance Measure for the Similarity Between the Fourier Transform of Time Series. 737-743
  
• Howard J. Hamilton, Kamran Karimi:
  The TIMERS II Algorithm for the Discovery of Causality. 744-750
  
• Yanchang Zhao, Chengqi Zhang, Shichao Zhang:
  A Recent-Biased Dimension Reduction Technique for Time Series Data. 751-757
  
• Jinhui Yuan, Bo Zhang, Fuzong Lin:
  Graph Partition Model for Robust Temporal Data Segmentation. 758-763
  
• Xinqiang Zuo, Xiaoming Jin:
  Accurate Symbolization of Time Series. 764-770
  
• Chotirat (Ann) Ratanamahatana, Eamonn J. Keogh, Anthony J. Bagnall, Stefano Lonardi:
  A Novel Bit Level Time Series Representation with Implication of Similarity Search and Clustering. 771-777
  
• Xingzhi Sun, Maria E. Orlowska, Xue Li:
  Finding Temporal Features of Event-Oriented Patterns. 778-784
  
• Ryohei Fujimaki, Takehisa Yairi, Kazuo Machida:
  An Anomaly Detection Method for Spacecraft Using Relevance Vector Learning. 785-790
  
• Tamás Horváth:
  Cyclic Pattern Kernels Revisited. 791-801
  

Text and Web Data Mining

• Liping Jing, Michael K. Ng, Jun Xu, Joshua Zhexue Huang:
  Subspace Clustering of Text Documents with Feature Weighting K-Means Algorithm. 802-812
  
• Chong Wang, Wenyuan Wang:
  Using Term Clustering and Supervised Term Affinity Construction to Boost Text Classification. 813-819
  
• Shin'ichi Kobayashi, Yasuyuki Shirai, Kazuo Hiyane, Fumihiro Kumeno, Hiroshi Inujima, Noriyoshi Yamauchi:
  Technology Trends Analysis from the Internet Resources. 820-825
  
• Jian-Wei Liu, Shou-Jian Yu, Jia-Jin Le:
  Dynamic Mining Hierarchical Topic from Web News Stream Data Using Divisive-Agglomerative Clustering Method. 826-831
  
• Leuo-hong Wang, Tong-Wen Lee:
  Collecting Topic-Related Web Pages for Link Structure Analysis by Using a Potential Hub and Authority First Approach. 832-837
  
• Jiankui Guo, Beijun Ruan, Zunping Cheng, Fang-zhong Su, Yaqin Wang, Xu-bin Deng, Ning Shang, Yangyong Zhu:
  A Top-Down Algorithm for Mining Web Access Patterns from Web Logs. 838-843
  
• Guang-Ho Cha:
  Kernel Principal Component Analysis for Content Based Image Retrieval. 844-849
  
• Atsuyoshi Nakamura, Mineichi Kudo:
  Mining Frequent Trees with Node-Inclusion Constraints. 850-860
  

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