List of Ideas from Afternoon Session of Drexel Workshop

• Drexel
  • Bachelor of Science in Information Systems, which is a five year program at Drexel, with 18 months of cooperative education in the five years
  • Masters of Science in Information Systems is a professional graduate degree primarily populated by IS professionals. It's applied computer science in a systems engineering framework. If I were giving it two more phrases, I would say, user-centered approach, user-centered design. Heavy emphasis on the user requirements part of the process. It is a software oriented degree.
  • Master of Science in Library and Information Science is the oldest degree program in the college. It was just named among the top ten by U.S. News and World Report , so it's a very well known and well respected program. It has been known for years as one of the leading, maybe the leading, program in terms of applied computing for the library field. One of the things it's known for.

    At the first two year level, we're recommending courses like linguistics and psychology and philosophy and logic...

• Ellen Voorhees
  • Agent development is key future area for IR. It needs 3 main supports:
  • Cognitive science: knowledge representation, both for the user models and for the ontology, the descriptions of the data resources. This leads to HCI several ways: How do you actually integrate those sorts of issues of this asynchronous communication between your computer and you? It also relates to the language or linguistics issues. And this gets back again into the indexing schemes, including multimedia.
  • Distributed applications: development of the computer infrastructure that will enable the agents, programming paradigms, program go to the resource instead of the resource coming to you. Also distributed AI: negotiation among agents, multi-agent systems.
  • Machine learning: automatic improvement of the user profiles and other resource descriptions, LSI indexing, data fusion. Developing scripts, programs that the agents follow.
• Edward A. Fox
  • For agents: AI, modeling or simulation techniques to begin to understand them, economic concerns
• W. B. Croft
  • Few computer science departments teach IR courses.
  • Need textbooks, industry funded chairs
  • Need collaborations between computer sciences business schools, information science and library schools and other schools too, some places there's a bit more emphasis on policy and economic policy and things like that or journalism schools ... departments like psychology...
  • When I say business information systems, I guess I meant more applying technology rather than learning how to build the technology, which is what computer science focuses on; more like applied computer science is a good way of putting it.
  • the issue of information retrieval being not mainstream.
  • Need hundreds of gigabytes of disk.
  • In the course I've taught, this is not part of our regular curriculum but I think you can cover most things that are interesting about IR, the fundamentals, in two courses-a sequence of two courses. The first course is an advanced undergraduate course which can serve as one course if you like, this is how to build IR systems. Not that everybody is going to go out and build IR systems. But it teaches you enough about the technology that they end up building their own IR systems. So they understand it, they can evaluate systems. They know what all the, really how things tick. And it also gives you enough scope to look at things like machine learning and other things like that. Sowe have one real core course and an advanced information retrieval course, so I'm just describing what our experience is. Other courses that information retrieval appears in: we have an internet course, tools on the internet, that's a low level course for the masters
• Larry Fitzpatrick
  • collaboration
  • higher level modeling of well understood tasks, different learning models for people
  • modeling personal organizational information consuming habits for better filtering
  • visualization
  • Scale
  • evaluation
  • Cross-pollinate