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» Extracting Web Data Using Instance-Based Learning
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ICML
2000
IEEE
14 years 11 months ago
Maximum Entropy Markov Models for Information Extraction and Segmentation
Hidden Markov models (HMMs) are a powerful probabilistic tool for modeling sequential data, and have been applied with success to many text-related tasks, such as part-of-speech t...
Andrew McCallum, Dayne Freitag, Fernando C. N. Per...
KES
2006
Springer
13 years 10 months ago
Web Site Off-Line Structure Reconfiguration: A Web User Browsing Analysis
The correct web site text content must be help to the visitors to find what they are looking for. However, the reality is quite different, many times the web page text content is a...
Sebastián A. Ríos, Juan D. Vel&aacut...
APWEB
2006
Springer
14 years 1 months ago
Image Description Mining and Hierarchical Clustering on Data Records Using HR-Tree
Since we can hardly get semantics from the low-level features of the image, it is much more difficult to analyze the image than textual information on the Web. Traditionally, textu...
Congle Zhang, Sheng Huang, Gui-Rong Xue, Yong Yu
WEBI
2005
Springer
14 years 3 months ago
A Middleware System for Web-Based Digital Music Libraries
We present a middleware system that facilitates Internet users’ access to web-based digital music libraries and allows them to manipulate audio meta-information taking into cons...
Aristomenis S. Lampropoulos, Paraskevi S. Lampropo...
ECTEL
2008
Springer
13 years 12 months ago
The Evolution of Social Ontologies
The idea of representing knowledge in formal models gets more and more popular. Since these models are understandable and thus processable by machines, the retrieval of knowledge i...
Nicolas Weber