Andy Gorman - Center for LifeLong Learning and Design6/14/01 S P I D E R Sharing Pertinent Information in Dynamically Evolving Repositories Projects generate large amounts of information –Proposals, Progress Reports, Results Projects comprised of loosely integrated teams need to keep members apprised of pertinent project information –Computer Science ETH,Clever,Social Assistant Project,CSLR –Cognitive Science Clever, CSLR –Health Sciences

Andy Gorman - Center for LifeLong Learning and Design6/14/01 Why is this important? because, “Innovation comes from outside the city walls.” - Kouichi Kishida, SRA to avoid duplicative work to increase social capital--who knows what? to create opportunities for more fluid collaboration (the type that can exists within a group)

Andy Gorman - Center for LifeLong Learning and Design6/14/01 Searching and Browsing “Ooooh, this is exciting! Our first practical application for the Internet! OK, should I do a search under ‘pythons,’ ‘snakes,’ or ‘suffocation’?”

Andy Gorman - Center for LifeLong Learning and Design6/14/01 How do we keep up with evolving information? Information delivery!

Andy Gorman - Center for LifeLong Learning and Design6/14/01 Approaches for Personalized Information Delivery Adaptable - the user can adapt the system to his or her needs (e.g., My Yahoo!) –Manber, U., Patel, A., & John, R. (2000). Experience with Personalization on Yahoo! Communications of the ACM, 43(8), ) Adaptive - system actively adapts to the user’s needs (e.g., Amazon.com) –Hirsh, h., Basu, C., & Davison, B. D. (2000). Learning to Personalize. Communications of the ACM, 43(8), –Mobasher, B., Cooley, R., & Srivastava, J. (2000). Automatic personalization based on Web usage mining. Communications of the ACM, 43(8),

Andy Gorman - Center for LifeLong Learning and Design6/14/01 BEA’s WebLogic Personalization Server Rule-based approach User Attributes – Enables the collection of metadata about users and their usage patterns –e.g., last login date, books purchased -> interest Classifier Rules –Classifies Users based on their attributes –e.g., recent user, Selection Rules - Matches content (based on meta data) to user class (based on attributes)

Andy Gorman - Center for LifeLong Learning and Design6/14/01 What’s the Problem? Rule-based approach is OK for e-commerce because content and users are well-categorized by marketing groups –E.g., Books -> Romance, Mystery,, etc. –E.g., Merchandise -> Automotive, Home Improvement, etc. Claim:Dynamic Information Repositories are too complex and large rule bases are unmanageable.

Andy Gorman - Center for LifeLong Learning and Design6/14/01 What’s the Solution? Some of the techniques mentioned are necessary but not sufficient Social Filtering - Amazon.com –“Dear Andrew Gorman, We have noticed that many of our customers who have purchased albums by Kenny Burrell also enjoy music by Miles Davis…” Semantic Analysis (LSA?) –“Here are things that are similar to the things you (or your group) have contributed.”

Andy Gorman - Center for LifeLong Learning and Design6/14/01 Who uses Information Repositories?

Andy Gorman - Center for LifeLong Learning and Design6/14/01 Social Factors affecting the adoption of information systems Disparity in work and benefit - “Who does the work and who receives the benefit?” Critical mass and Prisoner’s dilemma Disruption of social process Unobtrusive accessibility Adoption process - Grassroots roots vs.. Mandate Grudin, J. (1994). “Groupware and social dynamics: eight challenges for developers” Communications of the ACM, 37(1), )

Andy Gorman - Center for LifeLong Learning and Design6/14/01

Andy Gorman - Center for LifeLong Learning and Design6/14/01 Applications Group Collaboration (Coleman Institute) Extensible Library –Picture Library (I-Mail and MAPS) –Software (WebTogether) –Prompting Scripts (MAPS) Coleman Institute Portal