In this web, an increasing number of words surround the basic concept at a higher level. After identifying what each sentence is about, the system applies the same process to determine the main theme of each sentence, and it extends this to the paragraphs and the documents. ConText can be tuned by a user to provide different types of output. This tuning also allows a user to vary scanning patterns for different documents such as technical papers or editorial commentaries. The system offers a range of options from natural language processing down to word matching.
Proximity searching allows a user to find pairs of words separated by any number of unrelated words.
A medical researcher, for example, might want to extract documents where the word insulin appears three words away from the word diabetes. A fuzzy matching search allows for misspellings. Customers can store documents either in a flat file in the operating system or in a data base. After loading the documents, the user indexes them with a ConText mechanism and builds an application that employs this functionality. This application incorporates or omits functions, such as proximity search or theme search, according to user needs.