An Incremental Threshold Method for Continuous Text Search Queries

• Main Authors: MOURATIDIS, Kyriakos, PANG, Hwee Hwa
• Format: text
• Language: English
• Published: Institutional Knowledge at Singapore Management University 2009
• Subjects: Arrival rates; E-mail monitoring; Inverted files; Monitoring applications; Order of magnitude; Sliding Window; Structure-based; Text filtering; Text query; Text search; Threshold methods; User interests; User query; Databases and Information Systems; Numerical Analysis and Scientific Computing
• Online Access: https://ink.library.smu.edu.sg/sis_research/455; https://ink.library.smu.edu.sg/context/sis_research/article/1454/viewcontent/ICDE09_ConTextQueries.pdf
• Institution: Singapore Management University

A text filtering system monitors a stream of incoming documents, to identify those that match the interest profiles of its users. The user interests are registered at a server as continuous text search queries. The server constantly maintains for each query a ranked result list, comprising the recent documents (drawn from a sliding window) with the highest similarity to the query. Such a system underlies many text monitoring applications that need to cope with heavy document traffic, such as news and email monitoring. In this paper, we propose the first solution for processing continuous text queries efficiently. Our objective is to support a large number of user queries while sustaining high document arrival rates. Our solution indexes the streamed documents with a structure based on the principles of the inverted file, and processes document arrival and expiration events with an incremental threshold-based method. Using a stream of real documents, we experimentally verify the efficiency of our approach, which is at least an order of magnitude faster than a competitor constructed from existing techniques.