Stuart E. Madnick mainly investigates Information retrieval, Database, World Wide Web, Data mining and Disparate system. Stuart E. Madnick is interested in Semantic heterogeneity, which is a field of Information retrieval. Stuart E. Madnick has included themes like Interoperability and Management information systems in his Database study.
His work carried out in the field of World Wide Web brings together such families of science as Relational database and Cameleon. His Data mining study combines topics in areas such as Perspective, Information technology and Set. His Disparate system research is multidisciplinary, incorporating elements of Data transformation and Semantic interoperability.
His primary areas of study are Data science, Knowledge management, World Wide Web, Information retrieval and Database. His Data science research is multidisciplinary, incorporating perspectives in Metadata, Data integration, The Internet, Data quality and Bibliometrics. His research in Data quality intersects with topics in Information quality and Process.
His work investigates the relationship between Knowledge management and topics such as Mediation that intersect with problems in Interoperation. His Information retrieval study incorporates themes from Semantics and Data mining. His Database research is mostly focused on the topic Distributed database.
Stuart E. Madnick focuses on Computer security, Data science, Industrial control system, Mobilization and System dynamics. His Computer security study combines topics from a wide range of disciplines, such as Control and Information technology. His Information technology research incorporates themes from Concept map, Software development, Disaster recovery, Business continuity and Physical security.
His research integrates issues of Quality and Bibliometrics in his study of Data science. Stuart E. Madnick has researched Industrial control system in several fields, including Variable, Circuit breaker and Information technology management. In his research, Process, Organizational learning and Knowledge management is intimately related to Service-oriented architecture, which falls under the overarching field of System dynamics.
Stuart E. Madnick mainly focuses on Computer security, Knowledge management, Information technology, Flexibility and Key. The study incorporates disciplines such as Control, Iterative and incremental development and Systems thinking in addition to Computer security. His Knowledge management research includes themes of Marketing and Risk management.
The Information technology study combines topics in areas such as Concept map, Business continuity, Software development and Disaster recovery. The various areas that Stuart E. Madnick examines in his Flexibility study include Variable and Industrial control system. His work deals with themes such as Risk analysis, Chassis, Sociotechnical system, Isolation and Security analysis, which intersect with Key.
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Software Project Dynamics: An Integrated Approach
Tarek Abdel-Hamid;Stuart E. Madnick.
Overview and Framework for Data and Information Quality Research
Stuart E. Madnick;Richard Y. Wang;Yang W. Lee;Hongwei Zhu.
Journal of Data and Information Quality (2009)
Context interchange: new features and formalisms for the intelligent integration of information
Cheng Hian Goh;Stéphane Bressan;Stuart Madnick;Michael Siegel.
ACM Transactions on Information Systems (1999)
Data quality requirements analysis and modeling
R.Y. Wang;H.B. Kon;S.E. Madnick.
Data extraction from world wide web pages
Stuart E. Madnick;Michael D. Siegel.
Representing and reasoning about semantic conflicts in heterogeneous information systems
Cheng Hian Goh;Stuart E. Madnick.
Lessons learned from modeling the dynamics of software development
Tarek K Abdel-Hamid;Stuart E Madnick.
Communications of The ACM (1989)
The inter-database instance identification problem in integrating autonomous systems
J.R. Wang;S.E. Madnick.
international conference on data engineering (1989)
A Polygen Model for Heterogeneous Database Systems: The Source Tagging Perspective
Y. Richard Wang;Stuart E. Madnick.
very large data bases (1990)
A metadata approach to resolving semantic conflicts
Michael Siegel;Stuart E. Madnick.
Profile was last updated on December 6th, 2021.
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