As the amount of information and the number of Internet users grow, the problem of indexing and retrieval of electronic information resources becomes more critical. The existing search systems tend to generate misses and false hits due to the fact that they attempt to match the specified search terms without context in the target information resource. The COncordia INdexing and DIscovery system is an indexing system. It is a powerful means of helping users locate documents, software, and other types of data among large repositories. In environments that contain many different types of data, content indexing requires type-specific processing to extract information effectively.  The Semantic Header, which is proposed by Desai (11), contains the semantic contents of information resources. It provides a useful tool in searching for a document based on a number of commonly used criteria. The information from the semantic header could be used by the search system to help locate appropriate documents with minimum effort.  This thesis introduces an automatic tool for the extraction and storage of some of the meta-information in a Semantic Header and an automatic text classification scheme.