[UCI-Calit2] Upcoming Event: Calit2 Distinguished Lecture

Anna Lynn Spitzer aspitzer at rgs.uci.edu
Tue Feb 21 11:37:18 PST 2006


Title:                             From Search Engines to
Question-Answering Systems - The Problems of World Knowledge, Relevance,
Deduction and Precisiation

 

Speaker:                       Lotfi A. Zadeh, professor emeritus of
computer science, University of California, Berkeley, and director of
Berkeley Initiative in Soft Computing

 

Time:                            4:45 p.m. 

 

Date:                            Wednesday, March 1, 2006

            

Location:                       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 that existing
search engines do not have: deduction capability - the capability to
synthesize an answer to a query by drawing on bodies of information that
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 - tools 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
Zadeh's 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, which makes it
possible to deal effectively with information that is permanently
imprecise, uncertain and partially true.

 

Bio:                              Lotfi Zadeh is an alumnus of the
University of Tehran, MIT and Columbia University. He held visiting
appointments at the Institute for Advanced Study, MIT, IBM Research
Laboratory, SRI International, and the Center for the Study of Language
and Information. 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. Zadeh was awarded the IEEE Education
Medal in l973 and the IEEE Medal of Honor in l995.

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 has published more than 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 more than 60 journals. Zadeh is
known worldwide as the "Father of Fuzzy Logic."

 

Additional Information:    Faculty sponsor is Rui de Figueiredo.

 

 

 

 

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