Thesis (M.Sc.) - Cairo University - Faculty of Computers and Information - Department of Information Systems

Automatic document classification is one of theimportant tasks in web 3.0 due to the rapid growth of the number of electronic documents on the web available nowadays. Classification aims to assign the document to a predefined category automatically based on its contents. In general, text classification plays an important role in information extraction and summarization, text retrieval, question answering and web page content filtering. The Semantic Web aims to describe the meaning of information published on the Web to enable retrieval of information based on the accurate understanding of information{u2019}s semantics. Semantic Web plays a major role in enriching the web content where it allows user{u2019}s data to be linked from a source to another to be later understood by machines. Semantic annotation can be described as the tagging of an ontology class instance and mapping it to the corresponding ontology class so that data becomes meaningful.This will lead to classify objects based on theircontent. In addition to that, increment the number of metadata which describes the web content in an efficient manner, facilitates the searching via the web between machines on the web.Creating metadata is one of the major techniques that helps machines to understand and deal with data on thewebandcan be enriched using annotation. Semantic annotation is not only just used for enriching the data model information, but also it can be one of the useful solutions to help semi-automatic or even automatic systems interoperability

Issued also as CD