ICDM 2009 - PDF Preprint Papers

ICDM 2009 IEEE International Conference on Data Mining

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ICDM
2009
IEEE

259views Data Mining» more ICDM 2009»

Topic Modeling for Sequences of Temporal Activities

13 years 9 months ago

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: Topic Modeling for Sequences of Temporal Activities Zhi-Yong Shen, Ping Luo, Yuhong Xiong, Jun Sun, Yi-Dong Shen HP Laboratories HPL-2010-160 topic modeling, LDA, sequence, temp...

Zhiyong Shen, Ping Luo, Yuhong Xiong, Jun Sun, Yi-...

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Id	Views	Title	Status

1	259	Topic Modeling for Sequences of Temporal Activities	claim
2	254	Explore/Exploit Schemes for Web Content Optimization	claim
3	233	Semi-Supervised Sequence Labeling with Self-Learned Features	claim
4	223	Execution Anomaly Detection in Distributed Systems through Unstructured Log Analysis	claim
5	223	Differential Privacy for Clinical Trial Data: Preliminary Evaluations	claim
6	211	Discovering Organizational Structure in Dynamic Social Network	claim
7	207	Spatially Adaptive Classification and Active Learning of Multispectral Data with Gaussian Processes	claim
8	205	Active Selection of Sensor Sites in Remote Sensing Applications	claim
9	202	Link Prediction on Evolving Data Using Matrix and Tensor Factorizations	claim
10	200	Improving SVM Classification on Imbalanced Data Sets in Distance Spaces	claim
11	199	Active Learning with Adaptive Heterogeneous Ensembles	claim
12	198	Information Extraction for Clinical Data Mining: A Mammography Case Study	claim
13	197	A Linear-Time Graph Kernel	claim
14	188	Binomial Matrix Factorization for Discrete Collaborative Filtering	claim
15	184	Improved Multi Label Classification in Hierarchical Taxonomies	claim
16	183	Multirelational Topic Models	claim
17	181	Efficient Discovery of Frequent Correlated Subgraph Pairs	claim
18	176	SISC: A Text Classification Approach Using Semi Supervised Subspace Clustering	claim
19	175	Maximum Margin Clustering with Multivariate Loss Function	claim
20	174	Non-sparse Multiple Kernel Learning for Fisher Discriminant Analysis	claim
21	173	Discovery of Quantitative Sequential Patterns from Event Sequences	claim
22	172	Fine-Grain Perturbation for Privacy Preserving Data Publishing	claim
23	172	Sparse Least-Squares Methods in the Parallel Machine Learning (PML) Framework	claim
24	172	Evaluating Statistical Tests for Within-Network Classifiers of Relational Data	claim
25	171	Hybrid Clustering by Integrating Text and Citation Based Graphs in Journal Database Analysis	claim
26	169	Learning the Shared Subspace for Multi-task Clustering and Transductive Transfer Classification	claim
27	168	Bi-relational Network Analysis Using a Fast Random Walk with Restart	claim
28	167	A Framework for Computing the Privacy Scores of Users in Online Social Networks	claim
29	167	Self-Adaptive Anytime Stream Clustering	claim
30	165	Cross-Guided Clustering: Transfer of Relevant Supervision across Domains for Improved Clustering	claim
31	165	Audio Classification of Bird Species: A Statistical Manifold Approach	claim
32	164	iTopicModel: Information Network-Integrated Topic Modeling	claim
33	163	Kernel Conditional Quantile Estimation via Reduction Revisited	claim
34	162	Accurate Estimation of the Degree Distribution of Private Networks	claim
35	162	Towards a Universal Text Classifier: Transfer Learning Using Encyclopedic Knowledge	claim
36	162	The Flexible Climate Data Analysis Tools (CDAT) for Multi-model Climate Simulation Data	claim
37	161	Understanding Climate Change Patterns with Multivariate Geovisualization	claim
38	160	Fast Online Training of Ramp Loss Support Vector Machines	claim
39	156	Scalable Classification in Large Scale Spatiotemporal Domains Applied to Voltage-Sensitive Dye Imaging	claim
40	155	Stacked Gaussian Process Learning	claim
41	155	A Contrast Pattern Based Clustering Quality Index for Categorical Data	claim
42	154	Constraint-Based Pattern Mining in Dynamic Graphs	claim
43	154	GSML: A Unified Framework for Sparse Metric Learning	claim
44	153	A New Clustering Algorithm Based on Regions of Influence with Self-Detection of the Best Number of Clusters	claim
45	152	SLIDER: Mining Correlated Motifs in Protein-Protein Interaction Networks	claim
46	152	A Sparsification Approach for Temporal Graphical Model Decomposition	claim
47	151	TagLearner: A P2P Classifier Learning System from Collaboratively Tagged Text Documents	claim
48	150	Filtering and Refinement: A Two-Stage Approach for Efficient and Effective Anomaly Detection	claim
49	149	Accelerated Gradient Method for Multi-task Sparse Learning Problem	claim
50	148	VIF Regression: A Fast Regression Algorithm for Large Data	claim
51	148	Hierarchical Bayesian Models for Collaborative Tagging Systems	claim
52	148	Online System Problem Detection by Mining Patterns of Console Logs	claim
53	147	Greedy Optimization for Contiguity-Constrained Hierarchical Clustering	claim
54	146	A Walk from 2-Norm SVM to 1-Norm SVM	claim
55	146	Induction of Mean Output Prediction Trees from Continuous Temporal Meteorological Data	claim
56	145	Significance of Episodes Based on Minimal Windows	claim
57	143	An Attack on the Privacy of Sanitized Data that Fuses the Outputs of Multiple Data Miners	claim
58	142	Building Classifiers with Independency Constraints	claim
59	141	Discovering Excitatory Networks from Discrete Event Streams with Applications to Neuronal Spike Train Analysis	claim
60	141	Scalable Algorithms for Distribution Search	claim
61	141	Ensemble-Vis: A Framework for the Statistical Visualization of Ensemble Data	claim
62	139	A Bootstrap Approach to Eigenvalue Correction	claim
63	139	Towards Context Aware Food Sales Prediction	claim
64	139	Modeling Syntactic Structures of Topics with a Nested HMM-LDA	claim
65	139	Frequent Pattern Discovery from a Single Graph with Quantitative Itemsets	claim
66	138	Accurate Discovery of Valid Convoys from Moving Object Trajectories	claim
67	138	Semantic-Rich Markov Models for Web Prefetching	claim
68	138	Scalable Attribute-Value Extraction from Semi-structured Text	claim
69	137	Regression Learning Vector Quantization	claim
70	137	A Local Scalable Distributed Expectation Maximization Algorithm for Large Peer-to-Peer Networks	claim
71	137	A Deep Non-linear Feature Mapping for Large-Margin kNN Classification	claim
72	137	Set-Based Boosting for Instance-Level Transfer	claim
73	137	Argumentation Based Constraint Acquisition	claim
74	137	Analyzing Abnormal Events from Spatio-temporal Trajectories	claim
75	134	Efficient Discovery of Confounders in Large Data Sets	claim
76	133	On K-Means Cluster Preservation Using Quantization Schemes	claim
77	133	Clustering Trajectories of Moving Objects in an Uncertain World	claim
78	133	Pattern Mining over Star Schemas in the Onto4AR Framework	claim
79	132	Bayesian Overlapping Subspace Clustering	claim
80	131	Combining Super-Structuring and Abstraction on Sequence Classification	claim
81	131	Unified Solution to Nonnegative Data Factorization Problems	claim
82	130	Active Learning with Generalized Queries	claim
83	130	Efficient Anonymizations with Enhanced Utility	claim
84	129	Extended Boolean Matrix Decomposition	claim
85	129	GLSVM: Integrating Structured Feature Selection and Large Margin Classification	claim
86	127	Aspect Guided Text Categorization with Unobserved Labels	claim
87	126	Convex Non-negative Matrix Factorization in the Wild	claim
88	125	A Fully Automated Method for Discovering Community Structures in High Dimensional Data	claim
89	124	On the (In)Security and (Im)Practicality of Outsourcing Precise Association Rule Mining	claim
90	124	Rule Ensembles for Multi-target Regression	claim
91	124	A Practical Differentially Private Random Decision Tree Classifier	claim
92	122	Detecting and Interpreting Variable Interactions in Observational Ornithology Data	claim
93	121	Algorithms for Large, Sparse Network Alignment Problems	claim
94	121	Finding Time Series Motifs in Disk-Resident Data	claim
95	120	Least Square Incremental Linear Discriminant Analysis	claim
96	117	Discriminative Mixed-Membership Models	claim
97	117	Redistricting Using Heuristic-Based Polygonal Clustering	claim
98	117	Clustering with Multiple Graphs	claim
99	113	Connecting Sparsely Distributed Similar Bloggers	claim
100	113	Spatiotemporal Relational Random Forests	claim
101	112	Resolving Identity Uncertainty with Learned Random Walks	claim
102	112	Spatio-temporal Multi-dimensional Relational Framework Trees	claim
103	111	PEGASUS: A Peta-Scale Graph Mining System	claim
104	111	Permutation Tests for Studying Classifier Performance	claim
105	111	A Game Theoretical Model for Adversarial Learning	claim
106	111	To Trust or Not to Trust? Predicting Online Trusts Using Trust Antecedent Framework	claim
107	110	Finding Maximal Fully-Correlated Itemsets in Large Databases	claim
108	110	Projective Clustering Ensembles	claim
109	109	Knowledge Discovery from Citation Networks	claim
110	109	Finding Associations and Computing Similarity via Biased Pair Sampling	claim
111	109	Semi-naive Exploitation of One-Dependence Estimators	claim
112	108	RING: An Integrated Method for Frequent Representative Subgraph Mining	claim
113	107	Naive Bayes Classification of Uncertain Data	claim
114	105	Multi-document Summarization by Information Distance	claim
115	103	Unsupervised Relation Extraction by Massive Clustering	claim
116	102	Global Slope Change Synopses for Measurement Maps	claim
117	100	Conditional Models for Non-smooth Ranking Loss Functions	claim
118	98	Topic Distributions over Links on Web	claim
119	97	Hierarchical Probabilistic Segmentation of Discrete Events	claim
120	93	TubeTagger - YouTube-based Concept Detection	claim
121	92	Semi-supervised Multi-task Learning with Task Regularizations	claim
122	89	Discovering Domain Specific Concepts within User-Generated Taxonomies	claim

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