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CVIU
2004
115views more  CVIU 2004»
15 years 3 months ago
Dynamic learning from multiple examples for semantic object segmentation and search
We present a novel ``dynamic learning'' approach for an intelligent image database system to automatically improve object segmentation and labeling without user interven...
Yaowu Xu, Eli Saber, A. Murat Tekalp
MM
2004
ACM
151views Multimedia» more  MM 2004»
15 years 8 months ago
Affinity relation discovery in image database clustering and content-based retrieval
In this paper, we propose a unified framework, called Markov Model Mediator (MMM), to facilitate image database clustering and to improve the query performance. The structure of t...
Mei-Ling Shyu, Shu-Ching Chen, Min Chen, Chengcui ...
PKDD
1998
Springer
123views Data Mining» more  PKDD 1998»
15 years 7 months ago
Querying Inductive Databases: A Case Study on the MINE RULE Operator
Knowledge discovery in databases (KDD) is a process that can include steps like forming the data set, data transformations, discovery of patterns, searching for exceptions to a pat...
Jean-François Boulicaut, Mika Klemettinen, ...
BMCBI
2008
137views more  BMCBI 2008»
15 years 3 months ago
Evading the annotation bottleneck: using sequence similarity to search non-sequence gene data
Background: Non-sequence gene data (images, literature, etc.) can be found in many different public databases. Access to these data is mostly by text based methods using gene name...
Michael J. Gilchrist, Mikkel B. Christensen, Richa...
SIGMOD
2007
ACM
112views Database» more  SIGMOD 2007»
16 years 3 months ago
A random walk approach to sampling hidden databases
A large part of the data on the World Wide Web is hidden behind form-like interfaces. These interfaces interact with a hidden backend database to provide answers to user queries. ...
Arjun Dasgupta, Gautam Das, Heikki Mannila