Machine Learning for Information Extraction from XML marked-up text on the Semantic Web

From the perspective of a search engine, Information Extraction and the Semantic Web are complimentary ways toward achieving the same goal: helping the search engine to understand

FRED 4 [5] is an exception, since it is intended to produce semantic data and ontologies with a quality closer to what is expected at least from average linked datasets

To investigate the potential and suitability of language- processing-based approaches for semantic music information extraction from (Web-)texts, two strategies commonly used in

The definitions of the vague concepts of an ontology are automatically up- dated by validating the original ontology against a set of training axioms, thereby generating an

Keywords: Sentiment Analysis, Supervised Learning, Information Extraction, Machine Learning, Natural Language Processing, Arabic, Machine Translation?. 1

There exist many extraction tools that can process web pages and produce structured machine under- standable data (or information) that corresponds with the content of a web page..

Although many interesting approaches have been developed in the field of Trend Mining on texts, defined as Emerging Trend Detection in Text Mining[1], they are still lacking

Fragments of logical states will allow us to extract semantic information from Deep Web pages if we know the location of the state inside the navigation graph of the Web site..