World's Best Scientists 2026 revealed!
Richard J. Stevens

Richard J. Stevens

D-Index & Metrics

Computer Science

D-Index
39
Citations
5182
World Ranking
9885
National Ranking
4156

Overview

What is he best known for?

The fields of study he is best known for:

  • Database
  • Operating system
  • Programming language

His primary areas of study are Information retrieval, Logical data model, Theoretical computer science, Data mining and External Data Representation. Query optimization and Query expansion are among the areas of Information retrieval where the researcher is concentrating his efforts. The concepts of his Logical data model study are interwoven with issues in Field, Data abstraction and Database design.

His Data mining research includes themes of Computer program, Set and Relevance. His External Data Representation research is multidisciplinary, incorporating elements of Database schema and Information repository. His work deals with themes such as Abstraction layer, Data model and Component, which intersect with Information repository.

His most cited work include:

  • Application portability and extensibility through database schema and query abstraction (152 citations)
  • Secure database access through partial encryption (143 citations)
  • Process for data driven application integration for B2B (125 citations)

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

His scientific interests lie mostly in Information retrieval, Database, Data mining, Set and Theoretical computer science. His work on Query optimization, Query expansion and Question answering as part of general Information retrieval study is frequently connected to Sargable and Web query classification, therefore bridging the gap between diverse disciplines of science and establishing a new relationship between them. As part of his studies on Database, Richard J. Stevens often connects relevant subjects like Process.

His Data mining research is multidisciplinary, relying on both Field, Selection and Data access. As a part of the same scientific family, Richard J. Stevens mostly works in the field of Set, focusing on Workflow management system and, on occasion, Distributed computing. His Theoretical computer science study which covers Logical data model that intersects with External Data Representation and Abstraction layer.

He most often published in these fields:

  • Information retrieval (32.72%)
  • Database (29.01%)
  • Data mining (19.75%)

What were the highlights of his more recent work (between 2012-2021)?

  • Information retrieval (32.72%)
  • Artificial intelligence (8.02%)
  • Natural language processing (6.79%)

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

His main research concerns Information retrieval, Artificial intelligence, Natural language processing, Computer program and Natural language. His study ties his expertise on Set together with the subject of Information retrieval. His study looks at the relationship between Set and topics such as Data mining, which overlap with Selection.

His Natural language processing research is multidisciplinary, incorporating perspectives in Interpretation, Relevance and Presentation. His research in Computer program intersects with topics in Recommender system and World Wide Web. The Natural language study combines topics in areas such as Representation and Knowledge graph.

Between 2012 and 2021, his most popular works were:

  • Natural language processing ('nlp') (16 citations)
  • Analyzing Natural Language Questions to Determine Missing Information in Order to Improve Accuracy of Answers (12 citations)
  • Automatic Generation of Training Cases and Answer Key from Historical Corpus (9 citations)

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

  • Database
  • Operating system
  • Programming language

Richard J. Stevens focuses on Information retrieval, Artificial intelligence, Natural language processing, Questions and answers and Data structure. His studies deal with areas such as Interface, Set, Natural language and Association as well as Information retrieval. His study in Set is interdisciplinary in nature, drawing from both Data access, Data model, Column and Table.

His Artificial intelligence research incorporates themes from Fragment, Process, Truth value and Relevance. His work carried out in the field of Natural language processing brings together such families of science as Computer program and Feature. His research integrates issues of Granularity and Database in his study of Data structure.

Best Publications

  • Application portability and extensibility through database schema and query abstraction

    Richard Dean Dettinger;Peter John Johnson;Richard Joseph Stevens;Ikhua Tong

  • Secure database access through partial encryption

    Richard D. Dettinger;Frederick A. Kulack;Richard J. Stevens;Eric W. Will

  • Process for data driven application integration for B2B

    Terrence Ross O'Brien;William Craig Rapp;Richard Joseph Stevens

  • Graphical user interface for building queries with hierarchical conditions

    Richard Dean Dettinger;Peter John Johnson;Richard Joseph Stevens;Ikhua Tong

  • Method and system for providing aggregate data access

    Richard D. Dettinger;Richard J. Stevens;Jeffrey W. Tenner

  • Dealing with composite data through data model entities

    Richard D. Dettinger;Jennifer L. LaRocca;Richard J. Stevens;Jeffrey W. Tenner

  • Dynamic content generation/regeneration for a database schema abstraction

    Richard Dean Dettinger;Richard Joseph Stevens

  • Dynamic end user specific customization of an application's physical data layer through a data repository abstraction layer

    Richard Dean Dettinger;Richard Joseph Stevens

  • Remote data access and integration of distributed data sources through data schema and query abstraction

    Richard Dean Dettinger;Richard Joseph Stevens

  • Optimizing workflow execution against a heterogeneous grid computing topology

    Richard D. S. Dettinger;Cale T. Rath;Richard J. Stevens;Shannon E. Wenzel

  • Query abstraction high level parameters for reuse and trend analysis

    Richard D. Dettinger;Richard J. Stevens

  • Abstract data linking and joining interface

    Richard D. Dettinger;Cale T. Rath;Richard J. Stevens

  • Sequential stepwise query condition building

    Richard Dettinger;Daniel Kolz;Richard Stevens;Jeffrey Tenner

  • Auditing database access in a distributed medical computing environment

    Joel C. Dubbels;Janice R. Glowacki;Richard J. Stevens

  • Partial and parallel pipeline processing in a deep question answering system

    Adam T. Clark;Mark G. Megerian;John E. Petri;Richard J. Stevens

  • Metadata management for a data abstraction model

    Richard Dean Dettinger;Daniel Paul Kolz;Richard Joseph Stevens;Jeffrey Wayne Tenner

  • Iterative data analysis enabled through query result abstraction

    Richard D. Dettinger;Richard J. Stevens

  • Intelligent query re-execution

    Richard D. Dettinger;Richard J. Stevens;Jeffrey W. Tenner

  • Relationship management in a data abstraction model

    Richard D. Dettinger;Daniel P. Kolz;Richard J. Stevens;Shannon E. Wenzel

  • Intelligent evidence classification and notification in a deep question answering system

    Adam T. Clark;Mark G. Megerian;John E. Petri;Richard J. Stevens

Frequent Co-Authors

Eric L. Barsness
Eric L. Barsness IBM (United States)
John Matthew Santosuosso
John Matthew Santosuosso IBM (United States)

If you think any of the details on this page are incorrect, let us know.

Report an issue

We appreciate your kind effort to assist us to improve this page, it would be helpful providing us with as much detail as possible in the text box below:

Related Online Degrees & Career Pathways

Exploring Computer Science in the USA opens the door to numerous related online degrees and fast-evolving career pathways. One popular route is pursuing a graduate degree in data science. If affordability is a key concern, you may want to consider the cheapest data science masters in usa to maximize your return on investment.

Another in-demand option is electrical engineering, crucial for careers in tech and innovation. Flexible learning options like an online bachelor’s in electrical engineering allow you to study from anywhere while building foundational skills.

If you’re looking for quick credentials that can lead to high-paying jobs, there are plenty of easy certifications to get in tech and IT fields. These certifications are ideal for those seeking to enhance their resumes quickly and efficiently.

Time-conscious learners may also want to investigate the quickest masters degree online programs, which can help you advance in your career in the shortest amount of time possible.

Best Scientists Citing Richard J. Stevens

Trending Scientists

Recently Published Articles