ASHRAM: active summarization and Markup

Typically, searching for information in a document collection amounts to refining a query and then scanning a large number of documents to determine their relevance. Active Summarization Having Related Active Markup (ASHRAM) is a facility for representing and automatically selecting, marking, and linking useful and/or salient items in a document, to make it easier for the user to determine the main points in a document or navigate through documents without having to read all of them. ASHRAM is a novel client server system and user interface consisting of dynamically generated HTML, JavaScript and Java which requests information from a document database stored on a server. We describe a system for summarization by sentence extraction and a user interface for representation that allows the user to exploit the summary not only as an aid for relevance assessment of documents, but as an active aid to document navigation. The server-based scalable text summarization and keyword extraction system uses Natural Language Processing (NLP) technology and corpus-based NLP techniques in the foreground and databases constructed using NLP technology in the background.