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» Approximate data mining in very large relational data
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ICDE
2010
IEEE
295views Database» more  ICDE 2010»
15 years 8 months ago
K nearest neighbor queries and kNN-Joins in large relational databases (almost) for free
— Finding the k nearest neighbors (kNN) of a query point, or a set of query points (kNN-Join) are fundamental problems in many application domains. Many previous efforts to solve...
Bin Yao, Feifei Li, Piyush Kumar
KDD
2004
ACM
190views Data Mining» more  KDD 2004»
16 years 2 months ago
V-Miner: using enhanced parallel coordinates to mine product design and test data
Analyzing data to find trends, correlations, and stable patterns is an important task in many industrial applications. This paper proposes a new technique based on parallel coordi...
Kaidi Zhao, Bing Liu, Thomas M. Tirpak, Andreas Sc...
ICDM
2009
IEEE
137views Data Mining» more  ICDM 2009»
15 years 8 months ago
A Local Scalable Distributed Expectation Maximization Algorithm for Large Peer-to-Peer Networks
This paper offers a local distributed algorithm for expectation maximization in large peer-to-peer environments. The algorithm can be used for a variety of well-known data mining...
Kanishka Bhaduri, Ashok N. Srivastava
GISCIENCE
2004
Springer
130views GIS» more  GISCIENCE 2004»
15 years 7 months ago
Comparing Exact and Approximate Spatial Auto-regression Model Solutions for Spatial Data Analysis
The spatial auto-regression (SAR) model is a popular spatial data analysis technique, which has been used in many applications with geo-spatial datasets. However, exact solutions f...
Baris M. Kazar, Shashi Shekhar, David J. Lilja, Ra...
LWA
2008
15 years 3 months ago
Enhanced Services for Targeted Information Retrieval by Event Extraction and Data Mining
Where Information Retrieval (IR) and Text Categorization delivers a set of (ranked) documents according to a query, users of large document collections would rather like to receiv...
Felix Jungermann, Katharina Morik