[CPCC] TALK 3/1/2006 by L. Zadeh, UC Berkeley

[Ender Ayanoglu]

[This Calit2 Distinguished Lecture may be of interest to the CPCC
community.]
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            From Search Engines to Question-Answering Systems:
 The Problems of World Knowledge, Relevance, Deduction and Precisiation


                      Professor Lofti A. Zadeh
                 University of California, Berkeley
               Wednesday, Mar 1, 2006, 5:00 - 6:20PM
              McDonnell Douglas Engineering Auditorium

                             Abstract

Existing search engines, with Google at the top, have many truly
remarkable capabilities.  Furthermore, constant progress is being
made in improving their performance. But what is not widely recognized
is that there is a basic capability which existing search engines do
not have: deduction capability=ADthe capability to synthesize an answer
to a query by drawing on bodies of information which reside in various
parts of the knowledge base. By definition, a question-answering system
is a system which has deduction capability. Can a search engine be
upgraded to a question-answering system through the use of existing tools
=AD- tools which are based on bivalent logic and probability theory? A view
which is articulated in the following is that the answer is: No.

There are three major obstacles: (a) world knowledge; (b) relevance; and
(c) deduction. The problem with world knowledge is that in large measure
it is perception-based and hence is intrinsically imprecise. Example:
Usually it does not rain in San Francisco in midsummer. Perception-based
information is not available to manipulation through the use of bivalent
logic and probability theory.

The problem with relevance is that existing approaches to assessment of
relevance attempt to deal with relevance in a statistical framework,
with no consideration of semantics. The results leave much to be desired.

The problem with deduction is that in realistic settings the premises are
generally imprecise, uncertain and partially true. In such settings,
conventional methods of deduction do not work.

To deal with the problems of world knowledge, assessment of relevance and
deduction, new tools are needed. The new tools which are outlined in
my lecture are Precisiated Natural Language (PNL), Protoform Theory (PFT)
and Generalized Theory of Uncertainty (GTU). The centerpiece of these tools
is the concept of a generalized constraint. The concept of a generalized
constraint is what makes us possible to deal effectively with information
which is permanently imprecise, uncertain and partially true.


                       Speaker's Biography

Lotfi A. Zadeh is a Professor in the Graduate School, Computer Science
Division, Department of EECS, University of California, Berkeley. In
addition, he is serving as the Director of BISC (Berkeley Initiative in
Soft Computing). Lotfi Zadeh is an alumnus of the University of Tehran,
MIT and Columbia University. He held visiting appointments at the
Institute for Advanced Study, Princeton, NJ; MIT; IBM Research Laboratory,
San Jose, CA; SRI International, Menlo Park, CA; and the Center for the
Study of Language and Information, Stanford University. His earlier work
was concerned in the main with systems analysis, decision analysis and
information systems. His current research is focused on fuzzy logic,
computing with words and soft computing, which is a coalition of fuzzy
logic, neurocomputing, evolutionary computing, probabilistic computing and
parts of machine learning. As Chair of the Department of Electrical
Engineering at UC Berkeley from l963 to l968, Lotfi Zadeh has played a
major role in building up computer science and engineering programs within
the EE Department. In l967, on his initiative, the name of the Department
was changed to EECS. The Department of Electrical Engineering at UC was
the first in the world to change its name. In recognition of his
leadership in advancement of education in computer science and
engineering, Dr. Zadeh was awarded the IEEE Education Medal in l973. He
was awarded the IEEE Medal of Honor in l995.

Lotfi Zadeh is a Fellow of the IEEE, AAAS, ACM, AAAI, and IFSA. He is a
member of the National Academy of Engineering and a Foreign Member of the
Russian Academy of Natural Sciences, the Finnish Academy of Sciences, and
Polish Academy of Sciences, Korea Academy of Science & Technology and
Bulgarian Academy of Sciences. He is a recipient of the IEEE Medal of
Honor, the IEEE Education Medal, the IEEE Richard W. Hamming Medal, the
ASME Rufus Oldenburger Medal, the B. Bolzano Medal of the Czech Academy of
Sciences, the Kampe de Feriet Medal, the AACC Richard E. Bellman Control
Heritage Award, the Grigore Moisil Prize, the Honda Prize, the Okawa
Prize, the AIM Information Science Award, the IEEE-SMC J. P. Wohl Career
Achievement Award, the SOFT Scientific Contribution Memorial Award of the
Japan Society for Fuzzy Theory, the IEEE Millennium Medal, the ACM 2001
Allen Newell Award, the Norbert Wiener Award of the Systems, Man and
Cybernetics Society, Civitate Honoris Causa by Budapest Tech (BT)
Polytechnical Institution, Budapest, Hungary, the V. Kaufmann Prize,
International Association for Fuzzy-Set Management and Economy (SIGEF),
the Nicolaus Copernicus Medal of the Polish Academy of Sciences, the J.
Keith Brimacombe IPMM Award, other awards and twenty-three honorary
doctorates. He has published over 200 single-authored papers on a wide
variety of subjects relating to the conception, design and analysis of
information/intelligent systems, and is serving on the editorial boards of
over sixty journals. Lotfi Zadeh is known worldwide as the "Father of
Fuzzy Logic."

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