Central Knowledge Management System

With the advent of internet, corporate intranets and mass storage supports dissemination, there was a colossal increase of the amount of available data worldwide. Traditional Information Retrieval (IR) techniques became inadequate for the increasingly vast amounts of information, as only a small fraction of it would be relevant to a given individual. Individuals require modern IR frameworks to evaluate and rank the significance of the retrieved information, while uncovering better models for matching the user’s information needs with information that will satisfy their requirements. In order to pursue current Knowledge Management demands from actual corporations, an Information Retrieval system was developed in order to provide efficient indexing and full text searching features over a large collection of documents. This system was later improved with a Passage Retrieval mechanism, in order to retrieve portions of text instead of full documents. This is motivated by the fact that, as passages are ranked, users can be rapidly driven to the relevant information within the document. Finally, an evolutionary approach using Genetic Algorithms was integrated withi