  A server, which is to keep track of heavy document traffic, is unable to
filter the documents that are most relevant and updated for continuous text
search queries. This paper focuses on handling continuous text extraction
sustaining high document traffic. The main objective is to retrieve recent
updated documents that are most relevant to the query by applying sliding
window technique. Our solution indexes the streamed documents in the main
memory with structure based on the principles of inverted file, and processes
document arrival and expiration events with incremental threshold-based method.
It also ensures elimination of duplicate document retrieval using unsupervised
duplicate detection. The documents are ranked based on user feedback and given
higher priority for retrieval.
