Computing Reviews
Today's Issue Hot Topics Search Browse Recommended My Account Log In
Home Topics Titles Quotes Blog Featured Help
Jonathan P. E. Hodgson
St. Joseph's University
Philadelphia, Pennsylvania

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.


Evaluation of an automated knowledge-based textual summarization system for longitudinal clinical data, in the intensive care domain
Goldstein A., Shahar Y., Orenbuch E., Cohen M.  Artificial Intelligence in Medicine 82 20-33, 2017. Type: Article

This paper examines the potential of the Clinitext system [1] for the production of clinical summaries. Clinitext is designed to be general and not specific to any clinical domain; details on Clinitext are provided in [1]. In particular, the autho...


Low-rank decomposition meets kernel learning
Lan L., Zhang K., Ge H., Cheng W., Liu J., Rauber A., Li X., Wang J., Zha H.  Artificial Intelligence 250 1-15, 2017. Type: Article

This paper describes how low-rank kernel learning can be modified to make use of side information such as class labels on some of the data. In low-rank kernel learning, the kernel can be approximated using the Nystrom method in which a selection o...


Protein fold recognition based on sparse representation based classification
Yan K., Xu Y., Fang X., Zheng C., Liu B.  Artificial Intelligence in Medicine 79 1-8, 2017. Type: Article

It is not reasonable to expect the sequence of amino acids to predict folding because many proteins with similar foldings have quite different sequences. To address this issue, this paper describes how sparse representation classification (SRC) ca...


Building lexical resources for NLP
Derry Wijaya. YouTube, 00:55:28, published on May 21, 2017, Allen Institute for Artificial Intelligence (AI2), 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....


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...


Send Your Comments
Contact Us
Reproduction in whole or in part without permission is prohibited.   Copyright © 2000-2018 ThinkLoud, Inc.
Terms of Use
| Privacy Policy