Approximation algorithms for clustering uncertain data
Proceedings of the twenty-seventh ACM SIGMOD-SIGACT-SIGART symposium on Principles of database systems
Clustering Uncertain Data Via K-Medoids
SUM '08 Proceedings of the 2nd international conference on Scalable Uncertainty Management
Efficiently Clustering Probabilistic Data Streams
APWeb/WAIM '09 Proceedings of the Joint International Conferences on Advances in Data and Web Management
DTU: A Decision Tree for Uncertain Data
PAKDD '09 Proceedings of the 13th Pacific-Asia Conference on Advances in Knowledge Discovery and Data Mining
Probabilistic Granule-Based Inside and Nearest Neighbor Queries
ADBIS '09 Proceedings of the 13th East European Conference on Advances in Databases and Information Systems
Modeling and querying possible repairs in duplicate detection
Proceedings of the VLDB Endowment
Threshold-based probabilistic top-k dominating queries
The VLDB Journal — The International Journal on Very Large Data Bases
Metric spaces in data mining: applications to clustering
SIGSPATIAL Special
Data selection for exact value acquisition to improve uncertain clustering
WAIM'10 Proceedings of the 11th international conference on Web-age information management
Associative classifier for uncertain data
WAIM'10 Proceedings of the 11th international conference on Web-age information management
Similarity search and mining in uncertain databases
Proceedings of the VLDB Endowment
Kernel based K-medoids for clustering data with uncertainty
ADMA'10 Proceedings of the 6th international conference on Advanced data mining and applications: Part I
Evaluating the distance between two uncertain categorical objects
ADMA'10 Proceedings of the 6th international conference on Advanced data mining and applications - Volume Part II
Ranking uncertain sky: The probabilistic top-k skyline operator
Information Systems
Feature selection with mutual information for uncertain data
DaWaK'11 Proceedings of the 13th international conference on Data warehousing and knowledge discovery
Adjusting Fuzzy Similarity Functions for use with standard data mining tools
Journal of Systems and Software
Spatial query processing based on uncertain location information
DNIS'10 Proceedings of the 6th international conference on Databases in Networked Information Systems
Uncertain centroid based partitional clustering of uncertain data
Proceedings of the VLDB Endowment
Distance-based feature selection on classification of uncertain objects
AI'11 Proceedings of the 24th international conference on Advances in Artificial Intelligence
AN EFFICIENT REPRESENTATION MODEL OF DISTANCE DISTRIBUTION BETWEEN UNCERTAIN OBJECTS
Computational Intelligence
Nearest Neighbor-Based Classification of Uncertain Data
ACM Transactions on Knowledge Discovery from Data (TKDD)
Improving classification accuracy on uncertain data by considering multiple subclasses
AI'12 Proceedings of the 25th Australasian joint conference on Advances in Artificial Intelligence
Mining frequent serial episodes over uncertain sequence data
Proceedings of the 16th International Conference on Extending Database Technology
Distance-based feature selection from probabilistic data
WAIM'13 Proceedings of the 14th international conference on Web-Age Information Management
EMU: An expectation maximization based approach for clustering uncertain data
Journal of Intelligent & Fuzzy Systems: Applications in Engineering and Technology
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We study the problem of clustering data objects whose locations are uncertain. A data object is represented by an uncertainty region over which a probability density function (pdf) is defined. One method to cluster uncertain objects of this sort is to apply the UK-means algorithm, which is based on the traditional K-means algorithm. In UK-means, an object is assigned to the cluster whose representative has the smallest expected distance to the object. For arbitrary pdf, calculating the expected distance between an object and a cluster representative requires expensive integration computation. We study various pruning methods to avoid such expensive expected distance calculation.