Fast text searching: allowing errors
Communications of the ACM
Knowledge-based assistance for accessing large, poorly structured information spaces
Knowledge-based assistance for accessing large, poorly structured information spaces
The SIFT information dissemination system
ACM Transactions on Database Systems (TODS)
Modern Information Retrieval
Introduction to Modern Information Retrieval
Introduction to Modern Information Retrieval
Survey of Text Mining
SnoopIB: interval-based event specification and detection for active databases
Data & Knowledge Engineering
Events and streams: harnessing and unleashing their synergy!
Proceedings of the second international conference on Distributed event-based systems
High-performance composite event monitoring system supporting large numbers of queries and sources
Proceedings of the 5th ACM international conference on Distributed event-based system
Searching for complex patterns over large stored information repositories
BNCOD'11 Proceedings of the 28th British national conference on Advances in databases
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Information filtering includes monitoring text streams to detect patterns that are more complex than those handled by search engines. Text stream monitoring and pattern detection have far reaching applications such as tracking information flow among terrorist outfits, web parental control, and business intelligence. Pattern characterization requirements of applications entail an expressive language for specifying patterns than what is currently provided by Information Retrieval Query Languages (IRQLs) and current information filtering systems. Pattern specification alone does not suffice, as detecting these complex patterns is equally important in order to use these systems for real-world applications.InfoFilter, a content-based information filtering system, presented in this paper, allows users to specify complex patterns and detects these patterns in incoming text streams from various sources such as news feed, emails, web pages and caption text from streaming videos. Complex patterns such as combinations of sequential, structural patterns, wild cards, word frequencies, proximity, Boolean operators and synonyms are formulated using the expressive pattern specification language, PSL, proposed in this paper. Once specified, these complex patterns are detected using a data flow paradigm over Pattern Detection Graphs (PDGs).