ICDM 2006 - PDF Preprint Papers

ICDM 2006 IEEE International Conference on Data Mining

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ICDM
2006
IEEE

296views Data Mining» more ICDM 2006»

Fast Random Walk with Restart and Its Applications

13 years 11 months ago

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How closely related are two nodes in a graph? How to compute this score quickly, on huge, disk-resident, real graphs? Random walk with restart (RWR) provides a good relevance scor...

Hanghang Tong, Christos Faloutsos, Jia-Yu Pan

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Id	Views	Title	Status

1	296	Fast Random Walk with Restart and Its Applications	claim
2	227	Incremental Mining of Sequential Patterns over a Stream Sliding Window	claim
3	226	Converting Output Scores from Outlier Detection Algorithms into Probability Estimates	claim
4	225	Adaptive Kernel Principal Component Analysis with Unsupervised Learning of Kernels	claim
5	214	Forecasting Skewed Biased Stochastic Ozone Days: Analyses and Solutions	claim
6	193	Local Correlation Tracking in Time Series	claim
7	193	Feature Subset Selection on Multivariate Time Series with Extremely Large Spatial Features	claim
8	184	MARGIN: Maximal Frequent Subgraph Mining	claim
9	183	Accelerating Newton Optimization for Log-Linear Models through Feature Redundancy	claim
10	182	Active Learning to Maximize Area Under the ROC Curve	claim
11	176	Razor: mining distance-constrained embedded subtrees	claim
12	173	Trajectory Analysis for Soccer Players	claim
13	169	Privacy-Preserving Data Imputation	claim
14	166	Mining Generalized Graph Patterns Based on User Examples	claim
15	164	Unsupervised Learning of Tree Alignment Models for Information Extraction	claim
16	161	STAGGER: Periodicity Mining of Data Streams Using Expanding Sliding Windows	claim
17	161	Personalization in Context: Does Context Matter When Building Personalized Customer Models?	claim
18	161	Hierarchical Density Shaving: A clustering and visualization framework for large biological datasets	claim
19	158	GraphRank: Statistical Modeling and Mining of Significant Subgraphs in the Feature Space	claim
20	158	Detection of Interdomain Routing Anomalies Based on Higher-Order Path Analysis	claim
21	158	A Probability Distribution Of Functional Random Variable With A Functional Data Analysis Application	claim
22	155	Automatic Single-Organ Segmentation in Computed Tomography Images	claim
23	154	Mining and Predicting Duplication over Peer-to-Peer Query Streams	claim
24	153	Privacy-Preserving Data Linkage and Geocoding: Current Approaches and Research Directions	claim
25	153	k-STARs: Sequences of Spatio-Temporal Association Rules	claim
26	152	Application of Graph-based Data Mining to Metabolic Pathways	claim
27	151	Decision Trees for Functional Variables	claim
28	149	Pattern Mining in Frequent Dynamic Subgraphs	claim
29	149	P3C: A Robust Projected Clustering Algorithm	claim
30	148	Data Mining Approaches to Criminal Career Analysis	claim
31	147	Adaptive Parallel Graph Mining for CMP Architectures	claim
32	146	Boosting Kernel Models for Regression	claim
33	145	Stability Region Based Expectation Maximization for Model-based Clustering	claim
34	143	Applying Data Mining to Pseudo-Relevance Feedback for High Performance Text Retrieval	claim
35	143	A Comparison of Personal Name Matching: Techniques and Practical Issues	claim
36	140	Mining the Future: Predicting Itemsets' Support of Association Rules Mining	claim
37	139	Detecting Link Spam Using Temporal Information	claim
38	139	Privacy Preserving Nearest Neighbor Search	claim
39	139	Unsupervised Clustering In Streaming Data	claim
40	138	Adaptive Blocking: Learning to Scale Up Record Linkage	claim
41	138	Adding Semantics to Email Clustering	claim
42	138	Belief Propagation in Large, Highly Connected Graphs for 3D Part-Based Object Recognition	claim
43	137	Mining Complex Time-Series Data by Learning Markovian Models	claim
44	137	Automatic Construction of N-ary Tree Based Taxonomies	claim
45	135	SAXually Explicit Images: Finding Unusual Shapes	claim
46	135	Discovering Frequent Poly-Regions in DNA Sequences	claim
47	134	Biclustering Protein Complex Interactions with a Biclique Finding Algorithm	claim
48	134	Fast Frequent Free Tree Mining in Graph Databases	claim
49	133	An Experimental Investigation of Graph Kernels on a Collaborative Recommendation Task	claim
50	133	TRIAS - An Algorithm for Mining Iceberg Tri-Lattices	claim
51	132	High Quality, Efficient Hierarchical Document Clustering Using Closed Interesting Itemsets	claim
52	132	Mining for Tree-Query Associations in a Graph	claim
53	131	Intelligent Icons: Integrating Lite-Weight Data Mining and Visualization into GUI Operating Systems	claim
54	131	Dimension Reduction for Supervised Ordering	claim
55	131	A Maximum Likelihood Approach to Noise Estimation for Intensity Measurements in Biology	claim
56	131	A Method to Search ARX Model Orders and Its Application to Sales Dynamics Analysis	claim
57	131	Transforming Semi-Honest Protocols to Ensure Accountability	claim
58	130	Boosting for Learning Multiple Classes with Imbalanced Class Distribution	claim
59	130	A Framework for Regional Association Rule Mining in Spatial Datasets	claim
60	130	Efficient Clustering for Orders	claim
61	130	A Systemic Framework for the Field of Data Mining and Knowledge Discovery	claim
62	129	Getting the Most Out of Ensemble Selection	claim
63	129	Consensus Clustering for Detection of Overlapping Clusters in Microarray Data	claim
64	129	Keyword Generation for Search Engine Advertising	claim
65	128	delta-Tolerance Closed Frequent Itemsets	claim
66	127	The Relationships Among Various Nonnegative Matrix Factorization Methods for Clustering	claim
67	127	Optimal k-Anonymity with Flexible Generalization Schemes through Bottom-up Searching	claim
68	127	Predictive Integration of Gene Ontology-Driven Similarity and Functional Interactions	claim
69	124	Finding "Who Is Talking to Whom" in VoIP Networks via Progressive Stream Clustering	claim
70	123	Cluster Ranking with an Application to Mining Mailbox Networks	claim
71	122	Optimal Segmentation Using Tree Models	claim
72	122	Latent Friend Mining from Blog Data	claim
73	119	Direct Marketing When There Are Voluntary Buyers	claim
74	119	Fast On-line Kernel Learning for Trees	claim
75	118	GCA: A Coclustering Algorithm for Thalamo-Cortico-Thalamic Connectivity Analysis	claim
76	118	Generalizing Version Space Support Vector Machines for Non-Separable Data	claim
77	118	Reducing the Frequent Pattern Set	claim
78	117	Linear and Non-Linear Dimensional Reduction via Class Representatives for Text Classification	claim
79	116	Entity Resolution with Markov Logic	claim
80	116	Improving Personalization Solutions through Optimal Segmentation of Customer Bases	claim
81	115	Multi-Tier Granule Mining for Representations of Multidimensional Association Rules	claim
82	115	Concept-Aware Ranking: Teaching an Old Graph New Moves	claim
83	114	Incremental Mining of Frequent Query Patterns from XML Queries for Caching	claim
84	113	Mining Maximal Generalized Frequent Geographic Patterns with Knowledge Constraints	claim
85	111	Social Capital in Friendship-Event Networks	claim
86	110	Manifold Clustering of Shapes	claim
87	110	A mining method of communities keeping tacit knowledge	claim
88	109	Star-Structured High-Order Heterogeneous Data Co-clustering Based on Consistent Information Theory	claim
89	108	Minimum Enclosing Spheres Formulations for Support Vector Ordinal Regression	claim
90	108	Integrating Features from Different Sources for Music Information Retrieval	claim
91	108	Spatial Multidimensional Sequence Clustering	claim
92	107	Improving Grouped-Entity Resolution Using Quasi-Cliques	claim
93	105	Learning to Use a Learned Model: A Two-Stage Approach to Classification	claim
94	102	Who Thinks Who Knows Who? Socio-cognitive Analysis of Email Networks	claim
95	100	Meta Clustering	claim
96	100	Semantic Smoothing for Model-based Document Clustering	claim
97	98	What is the Dimension of Your Binary Data?	claim
98	95	TOP-COP: Mining TOP-K Strongly Correlated Pairs in Large Databases	claim
99	93	Comparisons of K-Anonymization and Randomization Schemes under Linking Attacks	claim
100	92	Window-based Tensor Analysis on High-dimensional and Multi-aspect Streams	claim
101	91	Exploratory Mining in Cube Space	claim
102	91	Entropy-based Concept Shift Detection	claim
103	91	Estimation System of People's Freindship and Hierarchical Relationship from Sentence Types	claim
104	89	Plagiarism Detection in arXiv	claim
105	89	Probabilistic Segmentation and Analysis of Horizontal Cells	claim
106	89	On the Lower Bound of Local Optimums in K-Means Algorithm	claim
107	86	Turning Clusters into Patterns: Rectangle-Based Discriminative Data Description	claim
108	86	Comparison of Descriptor Spaces for Chemical Compound Retrieval and Classification	claim
109	84	Exploratory Under-Sampling for Class-Imbalance Learning	claim
110	81	Full Perfect Extension Pruning for Frequent Graph Mining	claim
111	76	How Bayesians Debug	claim
112	76	A Probabilistic Ensemble Pruning Algorithm	claim

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