Download - 香港六合彩
Faculty
• Jacek Brzezinski• Robin Burke• Clark Elliott• Steven Lytinen• Craig Miller• Bamshad Mobasher
• Ashley Morris • Joseph Phillips• Daniela Raicu• Noriko Tomuro• Peter Wiemer-
Hastings
Research Areas/Projects (1)
• Intelligent Information Retrieval / Filtering– Web navigation (Miller)– WebACE (Mobasher)– ARCH (Mobasher, Lytinen, Miller)– FAQFinder (Tomuro, Lytinen)– Recommender systems (Burke)
• Intelligent Tutoring Systems, Cognitive Modeling– Miller– Wiemer-Hastings– Elliott
Research Areas/Projects (2)• Natural Language Processing
– Unification grammar and parsing (Tomuro, Lytinen)
– WordNet (Tomuro)– Latent Semantic Analysis (Wiemer-
Hastings)• Fuzzy GIS
– Morris• AI in Games
– Brzezinski
Robin Burke
• Recommender systems– Knowledge-based recommendation– Hybrid recommender systems– Interactive recommendation
• Applications in– Electronic Commerce: Intelligent product
catalogs– Digital Libraries: Intelligent multi-dimensional
browsing
Clark Elliott
• Emotion and Speech
– Natural Language Generation
– Natural Language Understanding
Steve Lytinen
• FAQFinder– with Noriko Tomuro– A natural language-based browser of
Frequently Asked Questions (FAQ) files • A Unification-based Natural Language Parser
– with Noriko Tomuro– Efficient parsing algorithms for a very
expressive grammar formalism called Unification Grammar
• ARCH– with Mobasher, Miller, Burke and Sieg– Document retrieval using concept hierearchy
Craig Miller
• User modeling to evaluate interfaces– in collaboration with NASA Ames
research labs – Modeling of navigation patterns/behavior
of web users– Evaluation of web site usability from a user's
perspective• Cognitive models of human learning
– A rule-based category-learning system that produces behavior consistent with human behavior
– Computational model of students interacting with an educational program (electrostatic physics)
Bamshad Mobasher
• Research Interests– Data mining and knowledge discovery
on the Web (Web Mining)– Intelligent agents for information retrieval / filtering – Agents for electronic commerce and automated
contracting• Projects
– Automatic Web Personalization based on Web Usage Mining
– MAGNET: Multi-agent distributed environment for automated contracting and supply-chain management
– WebACE: a client-side Web agent for document retrieval and categorization
Ashley Morris
• Using Fuzziness in Geographic Information Systems (GIS)
– Able to better store and represent spatial objects
• Fuzziness in data modeling
• Fuzzy learning systems
• http://morris2k.cti.depaul.edu/gis/FOOSBALL2.html
Joseph Phillips
• Computational Scientific Discovery– The field borrows from Philosophy of
Science, Machine Learning and Knowledge Discovery in Databases (KDD).
– Representing scientific knowledge – Automating scientific reasoning – Updating scientific models given data in databases – Visualizing models – Developing model building and preferencing criteria,
and defining heuristic functions over scientific models.
Daniela Raicu
• Content-based image retrieval
• Computer vision
• Data mining and knowledge discovery
• Machine learning
• Pattern recognition
Noriko Tomuro
• A Unification-based Natural Language Parser– with Steve Lytinen– Efficient parsing algorithms for a very expressive
grammar formalism called Unification Grammar• Computational Semantic Lexicon
– WordNet as the broad-coverage lexical resource• FAQFinder
– with Steve Lytinen– A natural language-based browser of Frequently
Asked Questions (FAQ) files
Peter Wiemer-Hastings• Research Interests
– Natural Language Understanding– Cognitive Modeling – Artificial Intelligence in Education
• Projects (more info at http://reed.cs.depaul.edu/peterwh)– SLSA: Hybrid symbolic and vector-based
natural language understanding– StoryStation: Helps children write better by
giving feedback from multiple agents– RMT: Research Methods Tutor, currently
used by DePaul Psychology students
Classes (CSC)• 3/457 (F) Expert Systems
– Learn how to make a rule-based system, and some theory
• 3/458 (Sp) Symbolic Programming– Learn Lisp and Prolog, basic AI langs
• 3/480 (W) Foundations of AI– Search, logic, inference, agents
• 578 (F) Machine Learning– ML and Neural Networks
• 587 (W) Cognitive Science– Computer models of cognitive tasks
Other Classes• DS/IS 575 (W) Intelligent Information
Retrieval– How to pull important info out of the web or
some other large collection• CSC 594 (Spr) Topics in AI
– This term: Topics in Knowledge Management (Burke)
• ITS 427 (Spr) Information Processing Models of Learning– Learn about how people learn
• ITS 580 (?) Artificial Intelligence in Learning Environments– Intelligence in Education
Questions?
