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» Learning from Highly Structured Data by Decomposition
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JMLR
2008
159views more  JMLR 2008»
14 years 10 months ago
Dynamic Hierarchical Markov Random Fields for Integrated Web Data Extraction
Existing template-independent web data extraction approaches adopt highly ineffective decoupled strategies--attempting to do data record detection and attribute labeling in two se...
Jun Zhu, Zaiqing Nie, Bo Zhang, Ji-Rong Wen
83
Voted
ER
2006
Springer
123views Database» more  ER 2006»
15 years 1 months ago
A Quantitative Summary of XML Structures
Statistical summaries in relational databases mainly focus on the distribution of data values and have been found useful for various applications, such as query evaluation and data...
Zi Lin, Bingsheng He, Byron Choi
ICML
2000
IEEE
15 years 11 months ago
Discovering Homogeneous Regions in Spatial Data through Competition
If all features causing heterogeneity were observed, a mixture of experts approach (Jacobs et al., 1991) is likely to be superior to using a single model. When unobserved or very n...
Slobodan Vucetic, Zoran Obradovic
ICDAR
2003
IEEE
15 years 3 months ago
Evaluating SEE - A Benchmarking System for Document Page Segmentation
The decomposition of a document into segments such as text regions and graphics is a significant part of the document analysis process. The basic requirement for rating and impro...
Stefan Agne, Andreas Dengel, Bertin Klein
CGO
2004
IEEE
15 years 1 months ago
Exposing Memory Access Regularities Using Object-Relative Memory Profiling
Memory profiling is the process of characterizing a program's memory behavior by observing and recording its response to specific input sets. Relevant aspects of the program&...
Qiang Wu, Artem Pyatakov, Alexey Spiridonov, Easwa...