Machine Learning for Sequential Data: A Review
Proceedings of the Joint IAPR International Workshop on Structural, Syntactic, and Statistical Pattern Recognition
Automatically Extracting Ontologically Specified Data from HTML Tables of Unknown Structure
ER '02 Proceedings of the 21st International Conference on Conceptual Modeling
Table extraction for answer retrieval
Information Retrieval
Extracting product features and opinions from reviews
HLT '05 Proceedings of the conference on Human Language Technology and Empirical Methods in Natural Language Processing
Learning field compatibilities to extract database records from unstructured text
EMNLP '06 Proceedings of the 2006 Conference on Empirical Methods in Natural Language Processing
Semantic annotation, indexing, and retrieval
Web Semantics: Science, Services and Agents on the World Wide Web
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Extraction of meaningful content from collections of web pages with unknown structure is a challenging task, which can only be successfully accomplished by exploiting multiple heterogeneous resources. In the Ex information extraction tool, so-called extraction ontologies are used by human designers to specify the domain semantics, to manually provide extraction evidence, as well as to define extraction subtasks to be carried out via trainable classifiers. Elements of an extraction ontology can be endowed with probability estimates, which are used for selection and ranking of attribute and instance candidates to be extracted. At the same time, HTML formatting regularities are locally exploited.