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Hodgson, Jonathan
St. Joseph's University
Philadelphia, Pennsylvania
 
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Dr. Jonathan Hodgson is a Professor of Mathematics and Computer Science at Saint Joseph's University in Philadelphia, PA, where he teaches a wide variety of courses at both the undergraduate and master's level. Previously, he was on the faculty at Adelphi University and, prior to that, at the University of Pennsylvania. Dr. Hodgson started his career as a mathematician working in the field of topology. He holds a Ph.D. in Mathematics from the University of Cambridge. Dr. Hodgson became involved with computers, originally with the idea of drawing pictures of knots on a Tektronix machine using Plot-90. In the 1980s, he developed an interest in artificial intelligence, particularly problem solving and logic programming, both of which are his areas of major research interest.

Dr. Hodgson has published papers on differential topology, problem solving, and the use of Hypertext Markup Language (HTML) tags for flagging semantic content in Web pages. He is currently the convenor of WG17, the ISO/IEC JTC1 working group on Prolog standardization.

 
 
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- 10 of 173 reviews

   
  Building lexical resources for NLP
Derry Wijaya. YouTube, 00:55:28, published on May 21, 2017, Allen Institute for Artificial Intelligence (AI2), https://www.youtube.com/watch?v=esYGSK3C3-M. Type: Video

This video comes from the Allen Institute for Artificial Intelligence (AI2) and first appeared on YouTube on May 21, 2017. The speaker addresses the problem of automating the extension of existing natural language processing (NLP) resources....

Aug 23 2017  
   A case-based reasoning system based on weighted heterogeneous value distance metric for breast cancer diagnosis
Gu D., Liang C., Zhao H.  Artificial Intelligence in Medicine 77 31-47, 2017. Type: Article

Case-based methods have previously been used to assist in treating cancers, and this paper introduces a number of significant modifications in the case of breast cancer. Specifically, these modifications relate to the way in which the distance bet...

Aug 3 2017  
  Knowledge base semantic integration using crowdsourcing
Meng R., Chen L., Tong Y., Zhang C.  IEEE Transactions on Knowledge and Data Engineering 29(5): 1087-1100, 2017. Type: Article

A major problem with integrating knowledge bases arises from the differing taxonomies underlying individual knowledge bases. Two nodes, one from each of a pair of taxonomies, may be related in one of four ways: they may be equivalent; the first ma...

Jul 12 2017  
  Recent contributions in intelligent systems
Sgurev V., Yager R., Kacprzyk J., Atanassov K.,  Springer International Publishing, New York, NY, 2016. 390 pp. Type: Book (978-3-319414-37-9)

This is a collection of the best papers from the 2012 IEEE Intelligent Systems Conference, which was held in Sofia, Bulgaria in September 2012. The average length of the papers in this volume is 20 pages. Since there are 20 papers in all, I will t...

May 25 2017  
   Assessing the epistemological relevance of Dung-style argumentation theories
Betz G.  Annals of Mathematics and Artificial Intelligence 78(3-4): 303-321, 2016. Type: Article

Phan Minh Dung described a model for argumentation in Artificial Intelligence in 1995 [1]. The model presents an argument framework as a collection of arguments together with an attack-relation defined on the set. A single argument
May 11 2017  
  Computing and restoring global inverse consistency in interactive constraint satisfaction
Bessiere C., Fargier H., Lecoutre C.  Artificial Intelligence 241(C): 153-169, 2016. Type: Article

When a constraint satisfaction problem requires or allows user interaction in the course of the solution, it is important that the solver prevent the user from selecting values for which no solution is possible. This might be the case where a user...

Apr 26 2017  
  Online bagging and boosting for imbalanced data streams
Wang B., Pineau J.  IEEE Transactions on Knowledge and Data Engineering 28(12): 3353-3366, 2016. Type: Article

Often in learning situations, the exceptional class that one seeks to learn forms a small proportion of the total, so that a conventional learning system that minimizes the error can easily fail to recognize the exceptional elements....

Feb 9 2017  
  Intelligent systems and applications: extended and selected results from the SAI Intelligent Systems Conference (IntelliSys) 2015
Bi Y., Kapoor S., Bhatia R.,  Springer International Publishing, New York, NY, 2016. 450 pp. Type: Book (978-3-319333-84-7)

This book is a collection of “extended and selected results” from the 2015 SAI Intelligent Systems Conference, held in London. Each of the 21 papers is about 20 pages in length. While the book is not formally divided into sections, the...

Jan 20 2017  
   Accelerating discovery: mining unstructured information for hypothesis generation
Spangler S.,  Chapman & Hall/CRC, Boca Raton, FL, 2015. 292 pp. Type: Book (978-1-482239-13-3)

The basic idea behind the “accelerated discovery” of this book’s title is that by using the ability of a computer to process large quantities of data, one can find interconnections that lead to new hypotheses. To take one example...

Nov 16 2016  
  Multiagent resource allocation for dynamic task arrivals with preemption
Doucette J., Pinhey G., Cohen R.  ACM Transactions on Intelligent Systems and Technology 8(1): 1-27, 2016. Type: Article

The authors describe a new approach to multiagent resource allocation problems. A typical problem would be the allocation of resources in an emergency room situation as new cases arrive continually. The model consists of four components: tasks, ta...

Sep 15 2016  
 
 
 
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