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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


  • 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


    • 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


    • 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

    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


    • 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 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


    • 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


    • 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

    • 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 !