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Computer Science Projects:
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Semantic Browsing
COLLS 499: Honors Thesis Research, Summer 2002, Fall 2002, and
Spring 2003
Faculty Advisor: Carl Lagoze, Cornell University Department of
Computer Science
This project provides a framework for annotating and reorganizing
existing files, pages, and sites on the Web that is similar to
Vannevar Bush's original concepts of trail blazing and associative
indexing. I have created several software applications that
allow users to both author and use Semantic Web metadata. To
create and use a layer of semantic content on top of the existing
Web, I have (1) implemented a user interface that expedites the
task of attributing metadata to resources on the Web, and (2)
augmented a Web browser to leverage this semantic metadata to
provide relevant information and tasks to the user.
ECDL 2003 Article
ECDL 2003 Presentation
Screen Shot: The Web Task Pane
Screen Shot: The Web Annotation Pane
Screen Shot: Site Annotator
Movie: Sequence Navigation
Movie: Downloading a Set of Images
Movie: Navigation on Semantic Links
Movie: Creating an RDF Triple
Movie: Creating an RDF Bag |
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A USENET Style Interface for
Peer-to-Peer Networks
CS 490: Independent Research, Spring 2002
Faculty Advisor: Carl Lagoze, Cornell University Department of
Computer Science
LimeWire, a popular Gnutella client written in Java, has pioneered
the use of rich XML queries to search the metadata of files
residing on the Gnutella network. The Gnutella network is strongly
search-centric. There is currently no way to browse through
information. Based on LimeWire's open source code, this project
used LimeWire's XML query engine to create a USENET style
interface on top of the Gnutella network.
Screen Shot
Paper
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Link
CS 501: Software Engineering, Spring 2003
Faculty Advisor: William Arms, Cornell University Department of
Computer Science
Project Team: Vincent Beurrier, Albert Eskenazi, Alex Faaborg,
Peter Flynn, Riaz Jahangir, Michael Sorokorensky, Jeff Yuen
As our project for CS 501 Software Engineering, my team created an
application to help intelligence analysts and law enforcement
officers with the task of Link Analysis. Our application was
designed to graphically represent associations between people,
telephone records, financial transaction records, and other
sources of information. The application allows analysts to import
subpoenaed database records (often coming from a telephone company
or financial institution), and provides tools for analysts to
create graphical visualizations from scratch. Data can be exported
as an XML file, making the application compatible with other Link
Analysis tools currently on the market.
My main role on the project team was based on Microsoft’s position
of Program Manager. I designed the application’s user interface
after conducting interviews with analysts, and understanding how
they did their job. My tasks included creating feature
specifications based on user requirements, prioritizing features
for our team’s developers, and tracking the team’s progress to
ensure that we reached all of our milestones and delivered the
application to our client on schedule.
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Search Engine
CS 430: Information Discovery, Fall 2002
Faculty Advisor: William Arms, Cornell University Department of
Computer Science
As the final assignment for CS 430, I created a search engine for
the Web. The search engine’s crawler uses multiple threads to
increase the speed at which it can index sections of the Web, and
respects robots.txt files. Parsed information is stored in an
inverted index, and term frequencies are calculated using a
standard tf.idf weighting scheme. The search and discover service
allows for Boolean and field-based searches, along with the
ability to browse forward and backward links. A
user interface
(a parody of everyone's favorite search engine) was added for
extra credit.
Screen Shot
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Leveraging Metadata for Natural
Language Processing
CS 473: Practicum in Artificial Intelligence, Fall 2001
Faculty Advisor: Bart Selman, Cornell University Department of
Computer Science
The single fastest way to locate information online, or in
any large body of documents, is with a text search. However, a
pure text search is lacking in many regards. Often, documents are
able to discuss topics while never directly stating them, or they
will use slightly different terminology. A pure text search will
scan documents for the occurrence of words, but it will follow no
particular logic or reason in the results it returns. Recently XML
and RDF have emerged to bring a semantic quality to information on
the Web. While any human can look at a web page and immediately
understand its semantics, XML and RDF are powerful because they
provide semantic information that is understandable to machines.
This project uses XML metadata to improve searching accuracy in
the form of an interactive chatbot that is both significantly more
intelligent than a pure text search, and provides a more natural
user experience.
Screen Shot
Cornell BOOM 2002
Poster
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Human Computer Interaction Projects:
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Using Neural Networks to Create an
Adaptive Character Recognition System
COGST 416: Modeling Perception and Cognition, Spring 2002
Faculty Advisor: Michael Spivey, Cornell University Department of
Psychology
A back-propagation neural network with one hidden layer was used
to create an adaptive character recognition system. The system was
trained and evaluated with printed text, as well as several
different forms of handwriting provided by both male and female
participants. Experiments tested (1) the effect of set size on
recognition accuracy with printed text, and (2) the effect of
handwriting style on recognition accuracy. Results showed reduced
accuracy in recognizing printed text when differentiating between
more than 12 characters. The handwriting style of the subjects had
varying and drastic effects on recognition accuracy which
illuminated some of the problems with the system's character
encoding.
Screen
Shot
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SamePage - Research In Real Time
Collaborative Applications
COMM 499: Independent Research, Spring 2001
Faculty Advisor: Geri Gay, Cornell University Human Computer
Interaction Group
Utilizing a network of client and server side applications
communicating with http tunneling, samePage is able to facilitate
real time push content and collaborative applications for use in
an educational environment.
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Leveraging Metadata to Improve
Information Retrieval in Directory Interfaces
COMM 499: Independent Research, , Fall 2001
Faculty Advisor: Geri Gay, Cornell University Human Computer
Interaction Group
This study describes how metadata can be used to organize
documents into hierarchical structures that filter against each
other. It then discusses several experiments that were conducted
to test the underlying usability concerns of this type of
organizational system.
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Computer Graphics and Vision Projects:
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A Psychophysical Study of BRDF
Based Lighting
COGST 201: Cognitive Science in Context, Spring 2001
Faculty Advisor: David Field, Cornell University Department of
Psychology
Subjects were presented with three-dimensional objects rendered
with BRDF-based lighting. The subjects were tested to see if (1)
the object they were looking at affected their ability to evaluate
an object's material and (2) if they were able to tell different
materials apart based only on light reflectance. Results showed
that even though most subjects felt like they were guessing,
subjects were able to correctly evaluate the object’s material
with about 70% accuracy. Readers should note that this study used
a reasonably small sample size that was not very unique
demographically.
Test Chalice
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Visual Acuity in Foveal and
Peripheral Vision
PSYCH 342: Human Perception: Applications to Computer Graphics,
Fall 2001
Faculty Advisor: David Field, Cornell University Department of
Psychology
We rarely notice that our peripheral vision is low resolution
because we are constantly focusing on what we want to look at with
our high resolution fovea. The muscles surrounding the eye allow
us to quickly scan our 2 degrees of foveal vision to whatever area
we need to view. Because of this, we are often completely unaware
of just how low resolution our peripheral vision is. This project
provides several interactive examples that demonstrate the
contrast in resolution between foveal and peripheral vision.
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Research at MIT |
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