clarke@csri.toronto.edu (Jim Clarke) (02/13/89)
(SF = Sandford Fleming Building, 10 King's College Road)
(GB = Galbraith Building, 35 St. George Street)
SUMMARY:
COLLOQUIUM - Tues., Feb. 28, 11 a.m. in Room SF 1105 -- Daniel Grayson
"Mathematica - A Program for symbolic Manipulation"
AI SEMINAR - Thurs., March 2, 11 a.m. in Room SF 1105 -- Dan Fass
"Collative Semantics: Main Assumptions, Features, and Implications"
SYSTEMS SEMINAR - Thurs., March 2, 2 p.m. in Room GB 305 -- Weidong Chen
"C-Logic of Complex Objects"
THEORY SEMINAR - Thurs., March 2, 3 p.m. in Room GB 244 -- Trevor J. Smedley
"A Fast Heuristic Method for Computations Involving Algebraic Numbers"
------------------------
COLLOQUIUM - Tuesday, February 28, 11 a.m. in Room SF 1105
Daniel Grayson
Universite of Illinois
"Mathematica - A Program for symbolic Manipulation"
Mathematica is a package for performing computations, numerical and symbol-
ic, and producing graphical representations of the results. I will explain
how we managed to create it in two years, explain some features of its
design, and give some examples of its use in mathematics.
AI SEMINAR - Thursday, March 2, 11 a.m. in Room SF 1105
Dan Fass
Simon Fraser University
"Collative Semantics: Main Assumptions, Features, and Implications"
Collative Semantics (CS) is a semantic theory for natural language process-
ing (NLP) which has been implemented in a computer program called meta5.
CS investigates word and sentence meaning in natural language, with exten-
sions towards the meaning of whole texts. The main features of CS rest on
its linguistic and theoretical assumptions. The main linguistic assump-
tions are that lexical ambiguity and what I call "semantic relations" are
essential to understanding word and sentence meaning. Seven kinds of seman-
tic relation are distinguished: literal, metonymic, metaphorical,
anomalous, redundant, inconsistent, and novel relations. Three main
theoretical assumptions are made:
[1] a division between knowledge and coherence (with a focus on the
latter),
[2] a framework of four theoretical constructs, including knowledge
representation and what I call "coherence representation" (the key to
modelling sentence meaning), and
[3] a linguistic view of knowledge representation (the way word meaning is
represented).
These assumptions will be described and the main features of CS will be
illustrated in the analysis of a metaphorical sentence. Some implications
of CS will be discussed through a contrast with other semantic theories in
NLP, notably Wilks' Preference Semantics (from which CS originally
developed) and the body of work based on Schank's Conceptual Dependency.
SYSTEMS SEMINAR - Thursday, March 2, 2 p.m. in Room GB 305
Weidong Chen
SUNY at Stony Brook
"C-Logic of Complex Objects"
In this talk I present a logic, called C-logic, for the natural representa-
tion and manipulation of complex objects. The development of complex
objects is a response to the criticism that relational database systems
(and logic programming systems) are too low-level to model complex real-
world entities naturally. However, in any more complex system, we would
like to retain the simple, elegant semantics that underlies relational sys-
tems, which makes them easy to understand and use.
C-Logic is a language that supports complex objects and has a simple
first-order semantics. The language supports object identities as terms
which can be constructed from constants and functions. It has a dynamic
notion of types, which corresponds to the concept of active domains in
databases. Multi-valued labels are inherent features of the logic. They are
more general than single-valued labels and support certain pragmatically
useful aspects of set manipulation. C-logic also provides a simple frame-
work for exploring efficient logic deduction over complex objects.
THEORY SEMINAR - Thursday, March 2, 3 p.m. in Room GB 244
Trevor J. Smedley
University of Waterloo
"A Fast Heuristic Method for Computations
Involving Algebraic Numbers"
Algorithms for doing computations involving algebraic numbers have
been known for quite some time[5,8,10] and implemen- tations now exist in
many computer algebra systems[1,3,9]. Many of these algorithms have been
analysed and shown to run in poly- nomial time and space[6,7], but in
spite of this many real prob- lems take large amounts of time and
space to solve. In this talk, I will review the standard algorithms for
computing with polynomials over an algebraic extension of the ration-
als, and describe a heuristic method which can be used for many operations
involving algebraic numbers[4]. The heuristic will not solve all instances
of these problems, but it returns either with the correct result or
with failure very quickly, and succeeds for a very large number of prob-
lems. The heuristic method is similar to, and based on concepts in[2].
I will also describe a method for extending the heuristic to perform alge-
braic number polynomial factorisation. A possible method for making the
heuristic into a probabilistic algorithm is also given, as well as a
method for extending the heuristic to work with multiple extension fields.
--
Jim Clarke -- Dept. of Computer Science, Univ. of Toronto, Canada M5S 1A4
(416) 978-4058
clarke@csri.toronto.edu or clarke@csri.utoronto.ca
or ...!{uunet, pyramid, watmath, ubc-cs}!utai!utcsri!clarke