PAKDD 2009 - PDF Preprint Papers

PAKDD 2009 Pacific-Asia Conference on Knowledge Discovery and Data Mining

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PAKDD
2009
ACM

107views Data Mining» more PAKDD 2009»

Accurate Synthetic Generation of Realistic Personal Information

1 years 6 months ago

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A large proportion of the massive amounts of data that are being collected by many organisations today is about people, and often contains identifying information like names, addre...

Peter Christen, Agus Pudjijono

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Id	Views	Title	Status
1	107	Accurate Synthetic Generation of Realistic Personal Information	claim
2	95	Change Analysis in Spatial Data by Combining Contouring Algorithms with Supervised Density Functions.	claim
3	70	Spatial Weighting for Bag-of-Visual-Words and Its Application in Content-Based Image Retrieval	claim
4	59	A Kernel Framework for Protein Residue Annotation	claim
5	57	Dynamic Exponential Family Matrix Factorization.	claim
6	56	Discovering Periodic-Frequent Patterns in Transactional Databases.	claim
7	55	Approximate Spectral Clustering.	claim
8	52	On Link Privacy in Randomizing Social Networks	claim
9	50	On Link Privacy in Randomizing Social Networks.	claim
10	49	On Mining Rating Dependencies in Online Collaborative Rating Networks	claim
11	49	Outlier Detection in Axis-Parallel Subspaces of High Dimensional Data	claim
12	48	Detecting Abnormal Events via Hierarchical Dirichlet Processes	claim
13	45	Pairwise Constrained Clustering for Sparse and High Dimensional Feature Spaces	claim
14	44	A Polynomial-Delay Polynomial-Space Algorithm for Extracting Frequent Diamond Episodes from Event Sequences	claim
15	43	Tree-Based Method for Classifying Websites Using Extended Hidden Markov Models	claim
16	42	Clustering with Lower Bound on Similarity	claim
17	41	Romanization of Thai Proper Names Based on Popularity of Usages	claim
18	40	A New Local Distance-Based Outlier Detection Approach for Scattered Real-World Data	claim
19	39	Detecting Link Hijacking by Web Spammers.	claim
20	39	When does Co-training Work in Real Data?	claim
21	38	Detecting Link Hijacking by Web Spammers	claim
22	36	Dynamic Exponential Family Matrix Factorization	claim
23	35	Data Mining for Intrusion Detection: From Outliers to True Intrusions	claim
24	34	Hot Item Detection in Uncertain Data	claim
25	34	Application-Independent Feature Construction from Noisy Samples	claim
26	34	Trace Mining from Distributed Assembly Databases for Causal Analysis	claim
27	33	Clustering Documents Using a Wikipedia-Based Concept Representation	claim
28	33	Budget Semi-supervised Learning	claim
29	31	Interval Data Classification under Partial Information: A Chance-Constraint Approach	claim
30	31	Item Preference Parameters from Grouped Ranking Observations	claim
31	31	Analysis of Variational Bayesian Matrix Factorization	claim
32	30	A Multi-resolution Approach for Atypical Behaviour Mining	claim
33	30	Scalable Web Mining with Newistic	claim
34	26	Aggregated Subset Mining	claim

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