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» Approximation algorithms for clustering uncertain data
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KDD
2006
ACM
156views Data Mining» more  KDD 2006»
14 years 8 months ago
Unsupervised learning on k-partite graphs
Various data mining applications involve data objects of multiple types that are related to each other, which can be naturally formulated as a k-partite graph. However, the resear...
Bo Long, Xiaoyun Wu, Zhongfei (Mark) Zhang, Philip...
JCDL
2006
ACM
161views Education» more  JCDL 2006»
14 years 1 months ago
Learning metadata from the evidence in an on-line citation matching scheme
Citation matching, or the automatic grouping of bibliographic references that refer to the same document, is a data management problem faced by automatic digital libraries for sci...
Isaac G. Councill, Huajing Li, Ziming Zhuang, Sand...
CORR
2010
Springer
162views Education» more  CORR 2010»
13 years 6 months ago
Networked Computing in Wireless Sensor Networks for Structural Health Monitoring
Abstract—This paper studies the problem of distributed computation over a network of wireless sensors. While this problem applies to many emerging applications, to keep our discu...
Apoorva Jindal, Mingyan Liu
JIIS
2006
147views more  JIIS 2006»
13 years 7 months ago
Mining sequential patterns from data streams: a centroid approach
In recent years, emerging applications introduced new constraints for data mining methods. These constraints are typical of a new kind of data: the data streams. In data stream pro...
Alice Marascu, Florent Masseglia
ICML
1994
IEEE
13 years 11 months ago
Prototype and Feature Selection by Sampling and Random Mutation Hill Climbing Algorithms
With the goal of reducing computational costs without sacrificing accuracy, we describe two algorithms to find sets of prototypes for nearest neighbor classification. Here, the te...
David B. Skalak