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R u le-b a s e d L o g ic-b a s e d F ra m e-b a s e d H y b ri d A n a lo g ic-b a s e d M e ta lo g ic-b a s e d M a n u fa c tu ri n g E le c tr o m e c h a n ic a l F in a n c ia l F lu id ic s C o n s tr u c ti o n S c h e d u le r C la s s if ie r P la n n e r D ia g n o s e r E v a lu a to r 2 M b y te s 3 M b y te s 6 M b y te s 2 M b y te s 1 0 M b(More)
The FinCEN* Artificial Intelligence System (FAR) links and evaluates reports of large cash transactions to identify potential money laundering. The objective of FAIS is to discover previously unknown, potential high value leads for possible investigation. FAIS integrates intelligent human and software agents in a cooperative discovery task on a very large(More)
This paper reports the first set of results from a comprehensive set of experiments to detect realistic insider threat instances in a real corporate database of computer usage activity. It focuses on the application of domain knowledge to provide starting points for further analysis. Domain knowledge is applied (1) to select appropriate features for use by(More)
Databases often inaccurately identify entities of interest. Two operations, consolidation and link formation, which complement the usual machine learning techniques that use similarity-based clustering to discover classifications, are proposed as essential components of KDD systems for certain applications. Consolidation relates identifiers present in a(More)
While much research has focused on methods for evaluating and maximizing the accuracy of classifiers either individually or in ensembles, little effort has been devoted to analyzing how classifiers are typically deployed in practice. In many domains, classifiers are used as part of a multi-stage process that increases accuracy at the expense of more data(More)
regulation advanced-detection system (ADS) monitors trades and quotations in The Nasdaq Stock Market to identify patterns and practices of behavior of potential regulatory interest. ADS has been in operational use at NASD Regulation since the summer of 1997 by several groups of analysts, processing approximately 2 million transactions a day, generating over(More)
CEN) AI system (FAIS) links and evaluates reports of large cash transactions to identify potential money laundering. The objective of FAIS is to discover previously unknown, potentially high-value leads for possible investigation. FAIS integrates intelligent human and software agents in a cooperative discovery task on a very large data space. It is a(More)
This paper reports on methods and results of an applied research project by a team consisting of SAIC and four universities to develop, integrate, and evaluate new approaches to detect the weak signals characteristic of insider threats on organizations' information systems. Our system combines structural and semantic information from a real corporate(More)