Sciweavers

104 search results - page 6 / 21
» Efficient Adaptive Retrieval and Mining in Large Multimedia ...
Sort
View
75
Voted
AMT
2006
Springer
108views Multimedia» more  AMT 2006»
14 years 11 months ago
Efficient Frequent Itemsets Mining by Sampling
As the first stage for discovering association rules, frequent itemsets mining is an important challenging task for large databases. Sampling provides an efficient way to get appro...
Yanchang Zhao, Chengqi Zhang, Shichao Zhang
SISAP
2010
IEEE
243views Data Mining» more  SISAP 2010»
14 years 7 months ago
Similarity matrix compression for efficient signature quadratic form distance computation
Determining similarities among multimedia objects is a fundamental task in many content-based retrieval, analysis, mining, and exploration applications. Among state-of-the-art sim...
Christian Beecks, Merih Seran Uysal, Thomas Seidl
166
Voted
VLDB
2001
ACM
146views Database» more  VLDB 2001»
15 years 9 months ago
Combining multi-visual features for efficient indexing in a large image database
Abstract. The optimized distance-based access methods currently available for multidimensional indexing in multimedia databases have been developed based on two major assumptions: ...
Anne H. H. Ngu, Quan Z. Sheng, Du Q. Huynh, Ron Le...
68
Voted
DASFAA
2009
IEEE
135views Database» more  DASFAA 2009»
15 years 1 months ago
Dimension-Specific Search for Multimedia Retrieval
Observing that current Global Similarity Measures (GSM) which average the effect of few significant differences on all dimensions may cause possible performance limitation, we prop...
Zi Huang, Heng Tao Shen, Dawei Song, Xue Li, Stefa...
SIGMOD
2001
ACM
184views Database» more  SIGMOD 2001»
15 years 9 months ago
Locally Adaptive Dimensionality Reduction for Indexing Large Time Series Databases
Similarity search in large time series databases has attracted much research interest recently. It is a difficult problem because of the typically high dimensionality of the data....
Eamonn J. Keogh, Kaushik Chakrabarti, Sharad Mehro...