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Personal Assistants for the Web: An MIT Perspective. Dep. Of Computer Science 95323-016 김광수. Introduction. The problem of information complexity Solution : Intelligent information agent Active assistance in finding and organizing information Like a human assistant

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personal assistants for the web an mit perspective

Personal Assistants for the Web:An MIT Perspective

Dep. Of Computer Science

95323-016 김광수

introduction
Introduction
  • The problem of information complexity
  • Solution : Intelligent information agent
    • Active assistance in finding and organizing information
    • Like a human assistant
  • The word “agent” : assistant
intelligent information agent
Intelligent Information Agent
  • Information in the Web
      • Highly unstructured
      • Natural language , pictures
  • Partial understanding

=> effective assistance to the user

information retrieval
Information Retrieval

- static databases, concentrated , organized in records

- a conversational paradigm( query, hits )

  • But, on the Web,Information Intelligent Agent

- hypertext, distributed, unstructured, non-textual information

- active, proactively trying to gather information even without the user’s explicit command

letizia
Letizia
  • information reconnaissance agent
  • It watches your Web browsing to try to learn what topics you are interested in.
  • It searches Semantic neighborhood of the current page to discover other pages you might be interested in
letizia1
Letizia
  • A co-operative venture between the user and Letizia
  • While you search “deep” (DFS)

, Letizia searches “wide” (BFS)

remembrance agent
Remembrance Agent
  • information reconnaissance agent
  • RA maintains the user’s personal information ( ex. the user’s e-mail, the set of files in the user’s home directory )
  • It shows messages that are relevant to the currently viewed text
slide10
An engineer reads email about a project
  • RA might remind her of project schedules, status reports, and other resources related to the project
let s browse
Let’s Browse
  • Allow a group to collaboratively browse together
  • Ex) business meeting , WebTV for family
  • By intersecting individual profiles of the users
  • A Letizia-like scan of a breadth-first neighborhood surrounding each user’s home page, or their organization’s home page
firefly
Firefly
  • Collaborative filtering agent
  • Every person says what items they like and dislike
  • New items are recommended to a user based on the opinions of people with similar taste
yenta
Yenta
  • Yenta introduces the users who share similar tastes to each other (match-making)
  • Yenta indexes e-mail & personal files like RA
  • Distributed, peer-to-peer communication, no central site
butterfly
Butterfly
  • A recommendation system for chat channels
  • The user converses with the Butterfly “chatterbot”
  • Butterfly periodically scans the thousands of available chat channels, sampling each only for a short time
expertfinder
ExpertFinder
  • EF assists with the problem of finding another user who is knowledgeable to answer a question
  • EF monitors a user’s activity within desktop applications
  • Ex) for Java programming
t te t te
Tête-à-Tête
  • Matchmaking between buyers and sellers in Electronic Commerce
  • The paradigm of integrative negotiation

- multiple dimensions rather than just price

the footprints sytem
The Footprints Sytem
  • “history-rich”
  • visualizing history-of-use in a complex information space
  • Nodes are documents (from any web site), links are traversals
information agents can be controversial
Information Agents Can be Controversial
  • It can make mistakes
  • But

- It can be used with conventional direct-manipulation software

- feedback between the user and the agent

  • Intelligent information agents can help the users !
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