Design team members: Justina Chan, Benjamin Gin
Supervisor: Prof. C. MacGregor
Background
Currently in the Internet age, vast amounts of information are available from numerous sources on all topics. However, to access the “right” information when the user desires it is becoming more difficult. The design of information retrieval systems matching the desire of the user is a challenging problem. When users are seeking or retrieving information, they might be looking for information that is conceptually related, and often, this information may not be lexically related. While in other cases, similar pieces of information may be described using different terms. Algorithms recognizing the underlying mappings of concepts are particularly useful. Disciplines such as Soft Computing aims to tackle this challenge. Neural Networks, one of the areas of Soft Computing, not only introduces technical advantages such as efficiency, accuracy and tolerance of errors, etc., as Harold Thimbleby puts it, neurocomputing makes “the computer become humble” [1]. Unlike conventional computing, neural computing system has to learn and adapt to the user rather the other way around. This makes the study of Human-Computer Interaction (HCI) more important in the development process than ever.
Project description
This workshop aims to examine the interrelationships between artificial intelligence and human-computer interaction. More specifically, it explores the area of incorporating human factors with the design of intelligent agent algorithms which provide filtered information related to the electronic calendar appointment entries entered by the user, based on the user’s profile generated by its preferences and activities.
The objectives of this workshop can be broken down into two areas:
1. The design and implementation of the intelligent algorithms:
Build
a
personal
profile
of
a
user
based
on
previous
activities
through
web
browser
history,
email
activities,
address
books
and
previous
appointments.
Creation
of
an
intelligent
agent
that
collects
URLs
for
appointments
in
the
calendar
based
on
the
user’s
profile.
Design
of
a
functional
graphical
user
interface
(GUI)
for
the
Intelligent
Calendar
to
display
appropriate
amount
of
information
to
the
users,
as
well
as
the
controls
of
the
features
of
the
agent
(e.g.
turning
on
and
off
the
searching
of
the
URLs).
2. Research questions related to user’s interactions with the calendar and its effects on the algorithm:
Given
the
data
and
profile
for
a
specified
user,
what
type
of
information
retrieved
by
the
agent
is
useful
from
the
user’s
perspective?
What
should
the
evaluation
and
validation
procedure
be
to
compare
the
suggestions
generated
by
the
intelligent
agent
to
the
user’s
“real”
preference?
What
possible
actions
or
tasks
might
the
user
perform
that
leads
to
more
reliable
data
on
a
user’s
preference
(e.g.
if
the
user
deletes
email
from
person
A,
does
that
mean
that
the
appointment
with
person
is
not
important?)?
Design methodology
This workshop adopts the spiral design model, which consists of the stages of analysis, design, implementation and testing. It is expected that at least four iterations will be executed.
First iteration
-
Analyze the problem and design high-level model of the system.
-
Present project proposal to professors and graduate students from the disciplines of HCI and Artificial Intelligence.
Second iteration
-
Analyze and research on area of intelligent agents and implementation tools.
-
Perform task analysis and research on human factors related to artificial intelligence.
-
Propose mock-up design of the user interface and perform design walkthroughs.
Third iteration
-
Evaluate alternatives of intelligent agent algorithm.
-
Perform functional testing on the final algorithms.
-
In parallel, implement standalone modules integrating with the chosen platform to identify potential roadblocks.
-
Refine user interface based on design walkthrough findings.
-
Conduct a study to collect information on how people relate and organize certain information conceptually.
Fourth iteration
-
Analyze and incorporate findings of previous testing in terms of efficiency and accuracy.
-
Implement the rest of the algorithms and features including the user interface.
-
Examine mapping of the intelligent agent system results to the user testing results.
-
Further design refinements and recommendations will be made until the criteria of the project are met.
Reference
[1] Beale, R., Finlay, J. Neural Networks and Pattern Recognition in Human-Computer Interaction. West Sussex, England: Ellis Horwood Limited, 1992.