Contextual Semantic: A Context-aware Approach for Semantic Web Based Data Extraction from Scientific Articles

The paper explores whether the semantic context is good enough to cope with ever increasing number of available resources in different repositories including the web. Here a problem of identifying authors of scientific papers is used as an example. A set of problem still do arise in case we apply exclusively the semantic context. Fortunately contextual semantic can be used to derive more information required to separate ambiguous cases. Semantic tags, well-structured documents and available databases of articles do provide a possibility to be more context-aware. Under the context we use co-authors names, references and headers to extract key-words and identify the subject. The real complexity of the considering problem comes from the dynamical behaviour of authors as they can change the topic of the research in the next paper. As the final judge the paper proposes applying words usage patterns analysis. Final the contextual intelligence engine is described.