Older Projects
Agents that work on a user's behalf at all touch-points - including
wireless devices - through which s/he interacts
with the web, and provide a range of personalized services
that are location, time and device format sensitive.
In addition to Intel's grant, we gratefully acknowledge their donation of two workstations,
valued at about $8K, to our lab.
Web Mining (supported by Intel, IBM, Neonyoyo/Interwoven, Accenture, Sulekha.com)
Analysis of web content (text and tags), hyperlink structure and usage of
web sites to better customize such sites to the needs of site-visitors. E-commerce
applications. Relating web analytics to system performance/availability.
Active Stereoscopic Visual Search (NSF)
Intrusion Detection, Network Management (Tivoli)
Detecting and modeling
change/deviations that may indicate computer security/integrity
problems.
Approximate Attribute Matching (HNC Software)
Finding similarities between XML documents, or between an XML query and a document.
Data Mining (Dell and KD1 (now part of NetPerceptions) )
Identifying and extracting useful information from reams of data and thus
facilitate smart business decisions. Applications to the computer industry
and e-commerce.
Multi-learner and Hybrid Intelligent Systems (funded by ARO, NSF).
Ensemble and hybrid networks; modular approaches for non-stationary problems;
multi-classifier systems; combining connectionist and symbolic techniques;
applications to difficult object recognition problems. Part of Center
for Imaging Science, a joint effort with Washington U., Harvard and
MIT.
Web Usage Analysis, User Profiling, Knowledge transfer and reuse (NSF)
Analyzing web logs, click-stream analysis, web metrics, recommender systems.
Use of knowledge developed in previous tasks to help in a new task. Design
of next-generation collaborative filters.
Modeling and Identification of Interacting Objects (Raytheon)
A spatio-temporal problem in which the sequence of symbols
emitted by an object may be affected by others in the vicinity.
Model Interpretation and Visualization
How can we understand what a neural network does? Rule extraction from
neural networks; theory refinement; visualization of network structure
and behavior; non-linear methods for dimensionality reduction.
Online
Demo of Radial Basis Function Network Toolkit
Classification and Clustering of Hyperspectral Data (NASA)
Working in high-dimensions; identifying land cover types from aerial images.
Robust Neural Networks and Pose Estimation (Phillips Lab)
Techniques for identifying outliers and atypical data, and for adapting to
dynamic environments. Pose estimation of space objects from image sequences.
Autonomous Intelligent Machines (TATP)
Particularly for navigating in hazardous environments and detection
environmental hazards.
Identification and Classification of spatio-temporal sequences (NSF/ONR /
Tracor)
Dynamic networks are being studied that make occasional judgements on input sequences, and cater to time alignment and dynamic time warping problems. Applied to short-duration underwater signals. A non-linear memory
structure based on habituation has been developed that has powerful
approximation capabilities.
Semiconductor Manufacturing (Motorola).
Modeling of various semiconductor manufacturing processes, and
prediction of chip quality.
Comparative performance of Static Classifiers (DARPA/ONR/Tracor)
This study includes practical techniques and
theoretical studies on network growth/pruning for valid generalization,
study of noise sensitivity of different networks, and performance on
limited, high dimensional inputs.
Our techniques have been successfully applied
to sonar and radar data, and for identification of defects in manufacturing
problems.
Forecasting/Prediction (Schlumberger)
Adaptive, non-linear regression techniques for forecasting desired response
given correlated parameters. Prediction of (chaotic) time series from past
samples. Applied to logging data from Schlumberger.
Data Mining of Student Records (UT)
Analysis of records of incoming UT students to predict course
loading etc., for improving future course offerings in the College of
Engineering.
Last Updated: April 1999
