Elaine Rich
Senior
Lecturer
The University of Texas at Austin
Taylor 3.126
ear@cs.utexas.edu
Office Hours: Wednesday 10:30 – 12:00, ACES 2.442
Recent, Current and
Upcoming Classes
K
-12 Outreach
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My most
recent project is a book entitled Automata, Computability and Complexity:
Theory and Applications. It was published by Prentice-Hall in September,
2007. The theoretical underpinnings of computing form a standard part of
almost every computer science curriculum. But the classic treatment of this
material isolates it from the myriad ways in which the theory influences the
design of modern hardware and software systems. My new book changes that. The main part of the book
is organized in the standard way: it begins with finite state machines and
regular languages. Next it covers context-free languages and it contains an
optional chapter on context-free parsing techniques. Then it introduces
Turing machines (and several equivalent models of computation) and the
question of undecidability. Finally, it considers the problem of practical
computability by introducing time and space complexity classes. For more
detail, see the the
book's website. Throughout the book there
are links to applications of the key concepts. A substantial appendix
describes many of those applications and pointers within the book to the book's website
describe others. Programming languages, compilers, networking, natural
language processing, artificial intelligence, computational biology,
security, and games are among the applications that are discussed. Instructors who choose to
use the book in their classes have access (through the Prentice-Hall site) to
a collection of resources designed to make it easy to teach from the book.
There is a complete set of Powerpoint slides, as well as answers to most of
the problems in the book and a set of additional problems (most with
solutions) that can be used for homeworks and exams. |
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I got a Ph.D. in CS in 1979
from CMU, with a dissertation, entitled Building
and Exploiting User Models. In that work, I showed that stereotypes (models
of groups of users who share common interests or characteristics) could be
effectively exploited by a system (mine was named Grundy) that gives advice to
people on things they might like. Grundy recommended novels to people, but the
same ideas can be used to recommend everything from music to cars. Two papers, one in IJMMS and one in Cognitive
Science, describe this work.
Grundy exploited relatively
deep models, both of the books it knew and of its users. This meant that the
models of the individual books had to be created by hand. And what about the
models of each user? The goal, in designing Grundy, was to minimize the amount
of interaction a user would have to have with Grundy in order to get going. To
achieve that goal, Grundy used stereotypes, which could be triggered for a
particular person just from a small set of words that the person provided as a
simple self description. Grundy generated book recommendations by comparing its
model of the current user to the models of the books it knew about. It chose
the best match and generated a short description of the book, which emphasized
the reasons it thought this user would like the book. Then it asked the user
whether it liked the recommendation, and, if not, why not. Using that feedback,
it updated both its stereotypes and its model of the current user.
Grundy's approach contrasts
with the now common technique known as collaborative filtering. In this latter
approach, the only thing that the system (for example, Amazon.com) knows about
its books is who bought them. The only thing it knows about an individual is
what books he or she has bought. It knows no reason why the person likes those
particular books. But it does know thousands of other people who liked the same
books and it knows which other books those people liked. So it can recommend
new books to a current user without any deep model either of the user's
preferences or of the books. Collaborative filtering systems substitute a
massive, shallow database for Grundy's smaller, deeper one.
While at CMU, I also did a
small project on the differences between men and women in their use of color terms.
Not surprisingly, women, on average, use a wider array of color expressions
than men do. See Sex-Related Colour Vocabulary
for the details.
When
I left CMU, I moved to
In the mid 80's, a noble
experiment called MCC was launched in
Now I'm back at UT, among
other things teaching Automata Theory (CS341) and Contemporary
Issues in Computer Science(CS 349).
Quilting
Sometime in the post knitting void, soon after finishing
the second AI book, I discovered quilting and got hooked. I can't talk about my
quilting, though, without pictures. So if you've got the time to download some
really nice photos, click on the quilt to visit my quilting page.
Links to Random
Presentations I've Put on the Web
- Debugging, the
Scientific Method, and Mastermind
- A Survey of
Nonpropositional Levels of Language Meaning and a Discussion of Some
Differences in the Way that Men and Women Talk
- The
Power and the Limits of Computation
- Gender and
Technology
- Mirrors
on Ourselves
- Easy, Hard,
Impossible
- ACM 101 –
English is Hard
- The CS
Elements Program