Ted E. Senator

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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)
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)
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)
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)
This paper describes a case study of an ongoing, deployed, KDD application – NASD Regulation’s Advanced Detection System (ADS), which monitors activity on the Nasdaq Stock Market – from the perspective of how organizations and systems are impacted by the continuous long-term use of KDD in a dynamic domain. It discusses knowledge management techniques that(More)
This article reviews a decade of progress in the area of link mining, focusing on application requirements and how they have and have not yet been addressed, especially in the area of complex event detection. It discusses some ongoing challenges and suggests ideas that could be opportunities for solutions. The most important conclusion of this article is(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)
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)