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ORCID10th ICDM 2010: Sydney, Australia
- Geoffrey I. Webb, Bing Liu, Chengqi Zhang, Dimitrios Gunopulos, Xindong Wu:
ICDM 2010, The 10th IEEE International Conference on Data Mining, Sydney, Australia, 14-17 December 2010. IEEE Computer Society 2010, ISBN 978-0-7695-4256-0
Keynote Abstracts
- Christos Faloutsos
:
Mining Billion-node Graphs: Patterns, Generators and Tools. 5 - Geoffrey J. McLachlan:
Assessing the Significance of Groups in High-Dimensional Data. 6 - Xindong Wu:
10 Years of Data Mining Research: Retrospect and Prospect. 7
Regular Papers
- James Abello, Tina Eliassi-Rad, Nishchal Devanur:
Detecting Novel Discrepancies in Communication Networks. 8-17 - Morteza Alamgir, Ulrike von Luxburg:
Multi-agent Random Walks for Local Clustering on Graphs. 18-27 - S. Tom Au, Rong Duan, Heeyoung Kim, Guangqin Ma:
Spatiotemporal Event Detection in Mobility Network. 28-37 - Tengfei Bao, Happia Cao, Enhong Chen, Jilei Tian, Hui Xiong:
An Unsupervised Approach to Modeling Personalized Contexts of Mobile Users. 38-47 - Kanishka Bhaduri, Qiang Zhu, Nikunj C. Oza, Ashok N. Srivastava:
Fast and Flexible Multivariate Time Series Subsequence Search. 48-57 - Alessandro Camerra, Themis Palpanas, Jin Shieh, Eamonn J. Keogh:
iSAX 2.0: Indexing and Mining One Billion Time Series. 58-67 - Cornelia Caragea, Adrian Silvescu, Doina Caragea, Vasant G. Honavar:
Abstraction Augmented Markov Models. 68-77 - Sharma Chakravarthy, Aravind Venkatachalam, Aditya Telang:
A Graph-Based Approach for Multi-folder Email Classification. 78-87 - Wei Chen, Yifei Yuan, Li Zhang:
Scalable Influence Maximization in Social Networks under the Linear Threshold Model. 88-97 - Alzennyr Da Silva, Raja Chiky, Georges Hébrail:
CLUSMASTER: A Clustering Approach for Sampling Data Streams in Sensor Networks. 98-107 - Bo Dai, Bao-Gang Hu, Gang Niu:
Bayesian Maximum Margin Clustering. 108-117 - Samik Datta, Anirban Majumder, Nisheeth Shrivastava:
Viral Marketing for Multiple Products. 118-127 - Timothy de Vries, Sanjay Chawla, Michael E. Houle:
Finding Local Anomalies in Very High Dimensional Space. 128-137 - Trong Dinh Thac Do, Anne Laurent, Alexandre Termier:
PGLCM: Efficient Parallel Mining of Closed Frequent Gradual Itemsets. 138-147 - Lan Du, Wray Lindsay Buntine, Huidong Jin:
Sequential Latent Dirichlet Allocation: Discover Underlying Topic Structures within a Document. 148-157 - Wouter Duivesteijn, Arno J. Knobbe, Ad Feelders, Matthijs van Leeuwen:
Subgroup Discovery Meets Bayesian Networks -- An Exceptional Model Mining Approach. 158-167 - Haytham Elghazel, Alex Aussem:
Feature Selection for Unsupervised Learning Using Random Cluster Ensembles. 168-175 - Zeno Gantner, Lucas Drumond, Christoph Freudenthaler, Steffen Rendle, Lars Schmidt-Thieme:
Learning Attribute-to-Feature Mappings for Cold-Start Recommendations. 176-185 - Yuanyuan Guo, Xiaoda Niu, Harry Zhang:
An Extensive Empirical Study on Semi-supervised Learning. 186-195 - Wilhelmiina Hämäläinen:
Efficient Discovery of the Top-K Optimal Dependency Rules with Fisher's Exact Test of Significance. 196-205 - Yue Han, Lei Yu:
A Variance Reduction Framework for Stable Feature Selection. 206-215 - Kohei Hayashi, Takashi Takenouchi, Tomohiro Shibata, Yuki Kamiya, Daishi Kato, Kazuo Kunieda, Keiji Yamada, Kazushi Ikeda:
Exponential Family Tensor Factorization for Missing-Values Prediction and Anomaly Detection. 216-225 - Jingrui He, Hanghang Tong, Jaime G. Carbonell:
Rare Category Characterization. 226-235 - Zhen Hu, Raj Bhatnagar:
Algorithm for Discovering Low-Variance 3-Clusters from Real-Valued Datasets. 236-245 - Sergey Ioffe:
Improved Consistent Sampling, Weighted Minhash and L1 Sketching. 246-255 - Peng Jiang, Chunxia Zhang, Hongping Fu, Zhendong Niu, Qing Yang:
An Approach Based on Tree Kernels for Opinion Mining of Online Product Reviews. 256-265 - Md. Enamul Kabir, Hua Wang, Yanchun Zhang:
A Pairwise-Systematic Microaggregation for Statistical Disclosure Control. 266-273 - Xiangnan Kong, Philip S. Yu:
Multi-label Feature Selection for Graph Classification. 274-283 - Takuro Kutsuna:
A Binary Decision Diagram-Based One-Class Classifier. 284-293 - Zhongmou Li, Hui Xiong, Yanchi Liu, Aoying Zhou:
Detecting Blackhole and Volcano Patterns in Directed Networks. 294-303 - Bo Liu, Jie Yin, Yanshan Xiao, Longbing Cao, Philip S. Yu:
Exploiting Local Data Uncertainty to Boost Global Outlier Detection. 304-313 - Jie Liu, Kai Yu, Yi Zhang, Yalou Huang:
Training Conditional Random Fields Using Transfer Learning for Gesture Recognition. 314-323 - Tantan Liu, Fan Wang, Gagan Agrawal:
Stratified Sampling for Data Mining on the Deep Web. 324-333 - Daniel Lowd, Jesse Davis:
Learning Markov Network Structure with Decision Trees. 334-343 - Dijun Luo, Chris H. Q. Ding, Heng Huang:
Towards Structural Sparsity: An Explicit l2/l0 Approach. 344-353 - Tengfei Ma, Xiaojun Wan:
Multi-document Summarization Using Minimum Distortion. 354-363 - Aditya Krishna Menon, Charles Elkan:
A Log-Linear Model with Latent Features for Dyadic Prediction. 364-373 - Pradeep Muthukrishnan, Dragomir R. Radev, Qiaozhu Mei:
Edge Weight Regularization over Multiple Graphs for Similarity Learning. 374-383 - Nam Nguyen:
A New SVM Approach to Multi-instance Multi-label Learning. 384-392 - Sunho Park, Seungjin Choi:
Bayesian Aggregation of Binary Classifiers. 393-402 - Sergey M. Plis, Terran Lane, Vince D. Calhoun:
Permutations as Angular Data: Efficient Inference in Factorial Spaces. 403-410 - Marko Pozenel, Viljan Mahnic, Matjaz Kukar:
Separation of Interleaved Web Sessions with Heuristic Search. 411-420 - Troy Raeder, T. Ryan Hoens, Nitesh V. Chawla:
Consequences of Variability in Classifier Performance Estimates. 421-430 - Parisa Rashidi, Diane J. Cook:
Mining Sensor Streams for Discovering Human Activity Patterns over Time. 431-440 - Piotr Rzepakowski, Szymon Jaroszewicz:
Decision Trees for Uplift Modeling. 441-450 - Eran Shaham, David Sarne, Boaz Ben-Moshe:
Co-clustering of Lagged Data. 451-460 - Jin Shieh, Eamonn J. Keogh:
Polishing the Right Apple: Anytime Classification Also Benefits Data Streams with Constant Arrival Times. 461-470 - Kelvin Sim, Zeyar Aung, Vivekanand Gopalkrishnan:
Discovering Correlated Subspace Clusters in 3D Continuous-Valued Data. 471-480 - Heli Sun, Jianbin Huang, Jiawei Han, Hongbo Deng, Peixiang Zhao, Boqin Feng:
gSkeletonClu: Density-Based Network Clustering via Structure-Connected Tree Division or Agglomeration. 481-490 - Liang Tang, Tao Li:
LogTree: A Framework for Generating System Events from Raw Textual Logs. 491-500 - Nikolaj Tatti, Boris Cule:
Mining Closed Strict Episodes. 501-510 - Kai Ming Ting, Jonathan R. Wells:
Multi-dimensional Mass Estimation and Mass-based Clustering. 511-520 - Xuan Vinh Nguyen, Julien Epps:
minCEntropy: A Novel Information Theoretic Approach for the Generation of Alternative Clusterings. 521-530 - Chang-Dong Wang, Jian-Huang Lai, Jun-Yong Zhu:
A Conscience On-line Learning Approach for Kernel-Based Clustering. 531-540 - Dingding Wang, Tao Li, Chris H. Q. Ding:
Weighted Feature Subset Non-negative Matrix Factorization and Its Applications to Document Understanding. 541-550 - Fei Wang, Ping Li, Arnd Christian König:
Learning a Bi-Stochastic Data Similarity Matrix. 551-560 - Xiang Wang, Ian Davidson:
Active Spectral Clustering. 561-568 - Xufei Wang, Lei Tang, Huiji Gao, Huan Liu:
Discovering Overlapping Groups in Social Media. 569-578 - Adam Woznica, Alexandros Kalousis:
Adaptive Distances on Sets of Vectors. 579-588 - Yanshan Xiao, Bo Liu, Longbing Cao, Jie Yin, Xindong Wu:
SMILE: A Similarity-Based Approach for Multiple Instance Learning. 589-598 - Jaewon Yang, Jure Leskovec:
Modeling Information Diffusion in Implicit Networks. 599-608 - Zi Yang, Wei Li, Jie Tang, Juanzi Li:
Term Filtering with Bounded Error. 609-618 - Min-Ling Zhang, Zhi-Hua Zhou:
Exploiting Unlabeled Data to Enhance Ensemble Diversity. 619-628 - Xianchao Zhang, Yao Wu, Yang Qiu:
Constraint Based Dimension Correlation and Distance Divergence for Clustering High-Dimensional Data. 629-638 - Yaling Zheng, Stephen Scott, Kun Deng:
Active Learning from Multiple Noisy Labelers with Varied Costs. 639-648 - Zeyu Zheng, Jun Yan, Shuicheng Yan, Ning Liu, Zheng Chen, Ming Zhang:
A Novel Contrast Co-learning Framework for Generating High Quality Training Data. 649-658 - Fang Zhou, Sébastien Mahler, Hannu Toivonen:
Network Simplification with Minimal Loss of Connectivity. 659-668 - Hang Zhou, Fabio T. Ramos, Eric Nettleton:
Improving Kernel Methods through Complex Data Mapping. 669-678 - Tianyi Zhou, Dacheng Tao, Xindong Wu:
NESVM: A Fast Gradient Method for Support Vector Machines. 679-688 - Yang Zhou, Hong Cheng, Jeffrey Xu Yu:
Clustering Large Attributed Graphs: An Efficient Incremental Approach. 689-698 - Qiang Zhu, Eamonn J. Keogh:
Mother Fugger: Mining Historical Manuscripts with Local Color Patches. 699-708 - Fuzhen Zhuang, Ping Luo, Zhiyong Shen, Qing He, Yuhong Xiong, Zhongzhi Shi:
D-LDA: A Topic Modeling Approach without Constraint Generation for Semi-defined Classification. 709-718
Short Papers
- Mohammad Al Hasan, Hilmi Yildirim, Abhirup Chakraborty:
SONNET: Efficient Approximate Nearest Neighbor Using Multi-core. 719-724 - Suhrid Balakrishnan, Sumit Chopra:
Two of a Kind or the Ratings Game? Adaptive Pairwise Preferences and Latent Factor Models. 725-730 - Ranieri Baraglia, Gianmarco De Francisci Morales, Claudio Lucchese:
Document Similarity Self-Join with MapReduce. 731-736 - Antonio Bella, César Ferri, José Hernández-Orallo, M. José Ramírez-Quintana:
Quantification via Probability Estimators. 737-742 - Xiongcai Cai, Michael Bain, Alfred Krzywicki, Wayne Wobcke, Yang Sok Kim, Paul Compton, Ashesh Mahidadia:
Learning Collaborative Filtering and Its Application to People to People Recommendation in Social Networks. 743-748 - Toon Calders, Calin Garboni, Bart Goethals:
Approximation of Frequentness Probability of Itemsets in Uncertain Data. 749-754 - Andrea Campagna, Rasmus Pagh:
On Finding Frequent Patterns in Event Sequences. 755-760 - Nicolas Cebron:
Active Improvement of Hierarchical Object Features under Budget Constraints. 761-766 - Shing-Kit Chan, Wai Lam:
Pseudo Conditional Random Fields: Joint Training Approach to Segmenting and Labeling Sequence Data. 767-772 - Bo Chen, Wai Lam, Ivor W. Tsang, Tak-Lam Wong:
Location and Scatter Matching for Dataset Shift in Text Mining. 773-778 - Xi Chen, Bing Bai, Yanjun Qi, Qihang Lin, Jaime G. Carbonell:
Learning Preferences with Millions of Parameters by Enforcing Sparsity. 779-784 - Robson Leonardo Ferreira Cordeiro, Fan Guo, Donna S. Haverkamp, James H. Horne, Ellen K. Hughes, Gunhee Kim, Agma J. M. Traina, Caetano Traina Jr., Christos Faloutsos:
QMAS: Querying, Mining and Summarization of Multi-modal Databases. 785-790 - Kamalika Das, Ashok N. Srivastava:
Block-GP: Scalable Gaussian Process Regression for Multimodal Data. 791-796 - Jun Du, Charles X. Ling:
Active Learning with Human-Like Noisy Oracle. 797-802 - Ad Feelders:
Monotone Relabeling in Ordinal Classification. 803-808 - George Giannakopoulos, Themis Palpanas:
The Effect of History on Modeling Systems' Performance: The Problem of the Demanding Lord. 809-814 - Fabian Gieseke, Gabriel Moruz, Jan Vahrenhold:
Resilient K-d Trees: K-Means in Space Revisited. 815-820 - Sertan Girgin, Jérémie Mary, Philippe Preux, Olivier Nicol:
Advertising Campaigns Management: Should We Be Greedy? 821-826 - Ben Goodrich, David W. Albrecht, Peter E. Tischer:
Accelerating Radius-Margin Parameter Selection for SVMs Using Geometric Bounds. 827-832 - Francesco Gullo, Carlotta Domeniconi, Andrea Tagarelli:
Enhancing Single-Objective Projective Clustering Ensembles. 833-838 - Francesco Gullo, Giovanni Ponti, Andrea Tagarelli:
Minimizing the Variance of Cluster Mixture Models for Clustering Uncertain Objects. 839-844 - Stephan Günnemann, Ines Färber, Brigitte Boden, Thomas Seidl:
Subspace Clustering Meets Dense Subgraph Mining: A Synthesis of Two Paradigms. 845-850 - Robert Gwadera:
Multi-stream Join Answering for Mining Significant Cross-Stream Correlations. 851-856 - Tsukasa Ishigaki, Takeshi Takenaka, Yoichi Motomura:
Category Mining by Heterogeneous Data Fusion Using PdLSI Model in a Retail Service. 857-862 - Santosh Kabbur, Eui-Hong Han, George Karypis:
Content-Based Methods for Predicting Web-Site Demographic Attributes. 863-868 - Faisal Kamiran, Toon Calders, Mykola Pechenizkiy:
Discrimination Aware Decision Tree Learning. 869-874 - U Kang, Mary McGlohon, Leman Akoglu, Christos Faloutsos:
Patterns on the Connected Components of Terabyte-Scale Graphs. 875-880 - Brendan Kitts, Liang Wei, Dyng Au, Amanda Powter, Brian Burdick:
Attribution of Conversion Events to Multi-channel Media. 881-886 - Neal Lathia, Jon Froehlich, Licia Capra:
Mining Public Transport Usage for Personalised Intelligent Transport Systems. 887-892 - Guangxia Li, Steven C. H. Hoi, Kuiyu Chang, Ramesh C. Jain:
Micro-blogging Sentiment Detection by Collaborative Online Learning. 893-898 - Junqiang Liu, Ke Wang:
Enforcing Vocabulary k-Anonymity by Semantic Similarity Based Clustering. 899-904 - Sen Liu, Chaolun Xia, Xiaohong Jiang:
Efficient Probabilistic Latent Semantic Analysis with Sparsity Control. 905-910 - Yanchi Liu, Zhongmou Li, Hui Xiong, Xuedong Gao, Junjie Wu:
Understanding of Internal Clustering Validation Measures. 911-916 - Mingsheng Long, Wei Cheng, Xiaoming Jin, Jianmin Wang, Dou Shen:
Transfer Learning via Cluster Correspondence Inference. 917-922 - Zhengdong Lu, Berkant Savas, Wei Tang, Inderjit S. Dhillon:
Supervised Link Prediction Using Multiple Sources. 923-928 - Mohammad M. Masud, Qing Chen, Latifur Khan, Charu C. Aggarwal, Jing Gao, Jiawei Han, Bhavani Thuraisingham:
Addressing Concept-Evolution in Concept-Drifting Data Streams. 929-934 - Pauli Miettinen:
Sparse Boolean Matrix Factorizations. 935-940 - Mario Navas, Carlos Ordonez, Veerabhadran Baladandayuthapani:
On the Computation of Stochastic Search Variable Selection in Linear Regression with UDFs. 941-946 - Vit Niennattrakul, Eamonn J. Keogh, Chotirat Ann Ratanamahatana:
Data Editing Techniques to Allow the Application of Distance-Based Outlier Detection to Streams. 947-952 - Keith Noto, Carla E. Brodley, Donna K. Slonim:
Anomaly Detection Using an Ensemble of Feature Models. 953-958 - Markus Ojala:
Assessing Data Mining Results on Matrices with Randomization. 959-964 - Nishith Pathak, Arindam Banerjee, Jaideep Srivastava:
A Generalized Linear Threshold Model for Multiple Cascades. 965-970 - Daniele Quercia, Neal Lathia, Francesco Calabrese, Giusy Di Lorenzo, Jon Crowcroft:
Recommending Social Events from Mobile Phone Location Data. 971-976 - Romain Quere, Hoel Le Capitaine, N. Fraisseix, Carl Frélicot:
On Normalizing Fuzzy Coincidence Matrices to Compare Fuzzy and/or Possibilistic Partitions with the Rand Index. 977-982 - Han Qin, Dejing Dou, Yue Fang:
Financial Forecasting with Gompertz Multiple Kernel Learning. 983-988 - Matthew J. Rattigan, David D. Jensen:
Leveraging D-Separation for Relational Data Sets. 989-994 - Steffen Rendle:
Factorization Machines. 995-1000 - Doruk Sart, Abdullah Mueen, Walid A. Najjar, Eamonn J. Keogh, Vit Niennattrakul:
Accelerating Dynamic Time Warping Subsequence Search with GPUs and FPGAs. 1001-1006 - Tim Schlüter, Stefan Conrad:
An Approach for Automatic Sleep Stage Scoring and Apnea-Hypopnea Detection. 1007-1012 - Stephan Seufert, Srikanta J. Bedathur, Julián Mestre, Gerhard Weikum:
Bonsai: Growing Interesting Small Trees. 1013-1018 - Mahdi Shafiei, Hugh A. Chipman:
Mixed-Membership Stochastic Block-Models for Transactional Networks. 1019-1024 - Hanhuai Shan, Arindam Banerjee:
Generalized Probabilistic Matrix Factorizations for Collaborative Filtering. 1025-1030 - Zhiyong Shen, Ping Luo, Shengwen Yang, Xukun Shen:
Topic Modeling Ensembles. 1031-1036 - Zhiyong Shen, Liang Du, Xukun Shen, Yi-Dong Shen:
Interval-valued Matrix Factorization with Applications. 1037-1042 - Xiaoxiao Shi, Wei Fan, Philip S. Yu:
Efficient Semi-supervised Spectral Co-clustering with Constraints. 1043-1048 - Xiaoxiao Shi, Qi Liu, Wei Fan, Philip S. Yu, Ruixin Zhu:
Transfer Learning on Heterogenous Feature Spaces via Spectral Transformation. 1049-1054 - Vikas Sindhwani, Serhat Selcuk Bucak, Jianying Hu, Aleksandra Mojsilovic:
One-Class Matrix Completion with Low-Density Factorizations. 1055-1060 - Jimeng Sun, Daby M. Sow, Jianying Hu, Shahram Ebadollahi:
A System for Mining Temporal Physiological Data Streams for Advanced Prognostic Decision Support. 1061-1066 - Xu Sun, Hisashi Kashima, Takuya Matsuzaki, Naonori Ueda:
Averaged Stochastic Gradient Descent with Feedback: An Accurate, Robust, and Fast Training Method. 1067-1072 - Daniel Svonava, Michail Vlachos:
Visualizing Graphs Using Minimum Spanning Dendrograms. 1073-1078 - Lu-An Tang, Xiao Yu, Sangkyum Kim, Jiawei Han, Chih-Chieh Hung, Wen-Chih Peng:
Tru-Alarm: Trustworthiness Analysis of Sensor Networks in Cyber-Physical Systems. 1079-1084 - Kilian Thiel, Michael R. Berthold:
Node Similarities from Spreading Activation. 1085-1090 - Hanghang Tong, B. Aditya Prakash, Charalampos E. Tsourakakis, Tina Eliassi-Rad, Christos Faloutsos, Duen Horng Chau:
On the Vulnerability of Large Graphs. 1091-1096 - Niko Vuokko, Petteri Kaski:
Testing the Significance of Patterns in Data with Cluster Structure. 1097-1102 - Fei Wang, Ping Li:
Compressed Nonnegative Sparse Coding. 1103-1108 - Ke Wang, Yabo Xu, Raymond Chi-Wing Wong, Ada Wai-Chee Fu:
Anonymizing Temporal Data. 1109-1114 - Zheng Wang, Yangqiu Song, Changshui Zhang:
Homotopy Regularization for Boosting. 1115-1120 - Jianshu Weng, Ee-Peng Lim, Qi He, Cane Wing-ki Leung:
What Do People Want in Microblogs? Measuring Interestingness of Hashtags in Twitter. 1121-1126 - Raymond Chi-Wing Wong, Ada Wai-Chee Fu, Ke Wang, Yabo Xu, Jian Pei, Philip S. Yu:
Probabilistic Inference Protection on Anonymized Data. 1127-1132 - Jun Wu, Mingyu Lu, Chun-Li Wang:
Collaborative Learning between Visual Content and Hidden Semantic for Image Retrieval. 1133-1138 - Yan Xie, Philip S. Yu:
Max-Clique: A Top-Down Graph-Based Approach to Frequent Pattern Mining. 1139-1144 - Qingyan Yang, Ju Fan, Jianyong Wang, Lizhu Zhou:
Personalizing Web Page Recommendation via Collaborative Filtering and Topic-Aware Markov Model. 1145-1150 - Hwanjo Yu, Sungchul Kim:
Passive Sampling for Regression. 1151-1156 - Jun Yu, Weng-Keen Wong, Rebecca A. Hutchinson:
Modeling Experts and Novices in Citizen Science Data for Species Distribution Modeling. 1157-1162 - Kui Yu, Xindong Wu, Hao Wang, Wei Ding:
Causal Discovery from Streaming Features. 1163-1168 - Chongsheng Zhang, Florent Masseglia, Yves Lechevallier:
ABS: The Anti Bouncing Model for Usage Data Streams. 1169-1174 - Peng Zhang, Xingquan Zhu, Jianlong Tan, Li Guo:
Classifier and Cluster Ensembles for Mining Concept Drifting Data Streams. 1175-1180 - Xianchao Zhang, Yansheng Jiang, Wenxin Liang, Xin Han:
Graph-Based Semi-supervised Learning with Adaptive Similarity Estimation. 1181-1186 - Xiangliang Zhang, Wei Wang, Kjetil Nørvåg, Michèle Sebag:
K-AP: Generating Specified K Clusters by Efficient Affinity Propagation. 1187-1192 - Yuan Zhang, Jie Tang, Jimeng Sun, Yiran Chen, Jinghai Rao:
MoodCast: Emotion Prediction via Dynamic Continuous Factor Graph Model. 1193-1198 - Li Zheng, Tao Li, Chris H. Q. Ding:
Hierarchical Ensemble Clustering. 1199-1204 - Jia Zou, Jing Xiao, Rui Hou, Yanqi Wang:
Frequent Instruction Sequential Pattern Mining in Hardware Sample Data. 1205-1210 - Huisheng Zhu, Peng Wang, Xianmang He, Yujia Li, Wei Wang, Baile Shi:
Efficient Episode Mining with Minimal and Non-overlapping Occurrences. 1211-1216
Tutorials
- Vania Bogorny, Shashi Shekhar:
Spatial and Spatio-temporal Data Mining. 1217 - Jun Huan:
Knowledge Discovery in Academic Drug Discovery Programs: Opportunities and Challenges. 1218 - Eamonn J. Keogh:
How to Do Good Data Mining Research and Get it Published in Top Venues. 1219 - Emmanuel Müller, Stephan Günnemann, Ines Färber, Thomas Seidl:
Discovering Multiple Clustering Solutions: Grouping Objects in Different Views of the Data. 1220
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