World's Best Scientists 2026 revealed!

D-Index & Metrics

Computer Science

D-Index
50
Citations
4866
World Ranking
5726
National Ranking
2598

Overview

What is he best known for?

The fields of study he is best known for:

  • Operating system
  • The Internet
  • Programming language

The scientist’s investigation covers issues in Data mining, Metadata, Inference, USable and Correctness. James R. Kraemer has included themes like Event, Chaotic, Set, Constraint and Cohort in his Data mining study. James R. Kraemer combines subjects such as Digital video, Real-time computing, World Wide Web and Customer identification with his study of Set.

His Cohort research incorporates themes from Computer program and Optimal control. His work in Metadata tackles topics such as Object which are related to areas like Pattern recognition and Video based. James R. Kraemer has researched Correctness in several fields, including Key, Information retrieval, Reliability and Database.

His most cited work include:

  • System and method to optimize control cohorts using clustering algorithms (87 citations)
  • System and method for deriving a hierarchical event based database optimized for analysis of biological systems (79 citations)
  • System and Method for Semantic Normalization of Healthcare Data to Support Derivation Conformed Dimensions to Support Static and Aggregate Valuation Across Heterogeneous Data Sources (78 citations)

What are the main themes of his work throughout his whole career to date?

James R. Kraemer spends much of his time researching Data mining, Computer program, Set, Database and Cohort. His research integrates issues of Event, Metadata, Inference and Information retrieval in his study of Data mining. His Metadata repository study in the realm of Metadata interacts with subjects such as USable.

His Inference course of study focuses on Correctness and Reliability. His Computer program research includes themes of Object, Event, Context based and Product. His work investigates the relationship between Set and topics such as Artificial intelligence that intersect with problems in Pattern recognition.

He most often published in these fields:

  • Data mining (33.79%)
  • Computer program (29.68%)
  • Set (28.31%)

What were the highlights of his more recent work (between 2013-2020)?

  • Computer program (29.68%)
  • Computer network (6.39%)
  • Set (28.31%)

In recent papers he was focusing on the following fields of study:

His primary areas of study are Computer program, Computer network, Set, Computer security and Protocol. His Computer program research includes elements of Process, Virtual machine, Software and Resource. His Computer network research is multidisciplinary, incorporating perspectives in Database transaction and Distributed computing.

His studies in Set integrate themes in fields like Data mining, Event, Cognition, Event and Computation. His Data mining research focuses on subjects like Product, which are linked to Object. In his research, Metadata is intimately related to Digital sensors, which falls under the overarching field of Event.

Between 2013 and 2020, his most popular works were:

  • Electronic Messaging Display Optimization (49 citations)
  • Secure management of a smart card (40 citations)
  • Generating deportment and comportment cohorts (40 citations)

In his most recent research, the most cited papers focused on:

  • Operating system
  • The Internet
  • Computer network

His main research concerns Computer program, Computer network, Object, Set and Distributed computing. His Computer program research is multidisciplinary, incorporating elements of Payload, Chip and Exclusive or. The various areas that James R. Kraemer examines in his Computer network study include Decentralized computing and Download.

His Object-oriented design, Method and Object model study, which is part of a larger body of work in Object, is frequently linked to USable, bridging the gap between disciplines. His Object-oriented design study combines topics in areas such as Data mining, Context model and Product. In his study, James R. Kraemer carries out multidisciplinary Set and Product research.

Best Publications

  • System and method for a multiple disciplinary normalization of source for metadata integration with ETL processing layer of complex data across multiple claim engine sources in support of the creation of universal/enterprise healthcare claims record

    Robert R. Friedlander;Richard A. Hennessy;James R. Kraemer

  • Inference of anomalous behavior of members of cohorts and associate actors related to the anomalous behavior

    Robert R. Friedlander;James R. Kraemer

  • System and method to optimize control cohorts using clustering algorithms

    Robert R. Friedlander;Richard A. Hennessy;James R. Kraemer;John Baxter Rollins

  • System and method for deriving a hierarchical event based database having action triggers based on inferred probabilities

    Robert R. Friedlander;Richard A. Hennessy;James R. Kraemer

  • System and method for deriving a hierarchical event based database optimized for analysis of biological systems

    Robert R. Friedlander;Richard A. Hennessy;James R. Kraemer

  • Generating Generalized Risk Cohorts

    Robert Lee Angell;Robert R. Friedlander;James R. Kraemer

  • Automatic generation of new rules for processing synthetic events using computer-based learning processes

    Robert Lee Angell;Robert R. Friedlander;James R. Kraemer

  • System and method for deriving a hierarchical event based database optimized for pharmaceutical analysis

    Robert R. Friedlander;Richard A. Hennessy;James R. Kraemer

  • System and method for deriving a hierarchical event based database optimized for clinical applications

    Robert R. Friedlander;Richard A. Hennessy;James R. Kraemer

  • System and method for deriving a hierarchical event based database optimized for analysis of criminal and security information

    Robert R. Friedlander;Richard A. Hennessy;James R. Kraemer

  • Synthetic Events For Real Time Patient Analysis

    Robert Lee Angell;Robert R. Friedlander;James R. Kraemer

  • Directing a user to a medical resource

    Robert R. Friedlander;Richard Hennessy;James R. Kraemer

  • Detecting behavioral deviations by measuring respiratory patterns in cohort groups

    Robert Lee Angell;James R. Kraemer

  • System and method of accident investigation for complex situations involving numerous known and unknown factors along with their probabilistic weightings

    Robert R. Friedlander;Richard A. Hennessy;James R. Kraemer

  • System and method for deriving a hierarchical event based database optimized for privacy and security filtering

    Robert R. Friedlander;Richard A. Hennessy;James R. Kraemer

  • Generating customized marketing messages using automatically generated customer identification data

    Robert Lee Angell;James R. Kraemer

  • Detecting behavioral deviations by measuring eye movements

    Robert Lee Angell;James R. Kraemer

  • System and method for deriving a hierarchical event based database optimized for analysis of complex accidents

    Robert R. Friedlander;Richard A. Hennessy;James R. Kraemer

  • System and method for the longitudinal analysis of education outcomes using cohort life cycles, cluster analytics-based cohort analysis, and probablistic data schemas

    Robert R. Friedlander;Jay A. Goodwyn;James R. Kraemer;Anthony W. Young

  • Generating Cohorts Based on Attributes of Objects Identified Using Video Input

    Robert Lee Angell;Sergio Borger;Robert R. Friedlander;James R. Kraemer

Frequent Co-Authors

Robert R. Friedlander
Robert R. Friedlander IBM (United States)
Robert Lee Angell
Robert Lee Angell IBM (United States)
David Ungar
David Ungar Apple (United States)
Mark N. Wegman
Mark N. Wegman IBM (United States)

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