We are interested in augmenting databases of bibliographic information with "cultural" information, specifically a family tree of the intellectual lineage of the authors of MS or PhD dissertations. Dissertations are substantial, topically-focused artifacts that are especially under the sway of the advisor's influence. We propose to test the use of such information, within the topical area of artificial intelligence In conjuction with bibliographic information about the AI literature, can be used to characterize important intellectual developments within AI, and thereby provide evidence about general processes of scientific discovery. The focus on dissertations is certainly not meant to suggest that only people with (MS or PhD) graduate degrees are involved in AI research. Rather, it is a simplification designed to make the notion of intellectual "lineage" more precise.
If you have completed a masters or Ph.D. thesis and consider yourself a researcher in AI, I would like you to send me information about where you got your degree, who your advisor and committee members were, and where you have worked since then. Also, please forward this query to any of your colleagues that may not see this mailing list. The specific questions are contained in a brief questionnaire below, and this is followed by an example. I would appreciate it if you could fill in the form below. (Currently this form is sent using the MAILTO action, which has only been tested on Netscape browsers.)
If you know some of these facts about your advisor (or other committee members), their advisors, etc., I would appreciate it if you could send me that information as well. One goal is to trace the genealogy of today's researchers back as far as possible (for example, to participants in the Dartmouth conference of 1956), as well as connections to other disciplines.
Previous iterations of this AIGeneology query have gone out in 1992 and 1994; the current corpus contains information on approximately 5000 dissertations. One interesting change that the maturing WWW has brought is increased concerns about both privacy and spoofing. Regarding the first concern, if you would like to have information about your dissertaton removed from this resource, please send an Email message (from a verifiable user account) and it will be removed immediatey. All new entries submitted via this form must include a verifiable Email address for both the author and his/her advisor.
Author's name Richard K. Belew
Current Email address rik@cs.ucsd.edu
Dissertation type PhD
Dissertation year 1986
Dissertation title Adaptive information retrieval machine learning
in associative networks
Language English
Department Computer & Communication Sciences (CCS)
University University of Michigan
Univ. address Ann Arbor, Michigan 48103
Co-advisor Stephen Kaplan
Advisor's department Psychology
Co-advisor Paul D. Scott
Advisor2's department Computer & Communication Sciences (CCS)
Committee member Michael D. Gordon
Member's department Mgmt. Info. Systems - Business School
Committee member John H. Holland
Member's department Computer & Communication Sciences (CCS)
Committee member Robert K. Lindsay
Member's department Psychology
Current workplace CSE Dept., UCSD (cs.ucsd.edu)
Institution's address La Jolla, CA 92093
Begin Date 9/1/86
EndDate present
Last updated by rik on 7 Mar 99.