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Personalizing the Web

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Machine learning and Intelligent Systems. Integrated Internet. References ... [7] Ed H. Chi, Peter Pirolli, Kim Chen, James Pitkow. ... – PowerPoint PPT presentation

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Title: Personalizing the Web


1
Personalizing the Web
  • Todd Lanning
  • Project 1 - Presentation
  • CSE 8331
  • Dr. M. Dunham

2
A Little Motivation
  • Size of the Web
  • Equal Proximity
  • Shift in Internet usage (once academic focus)

3
Introduction
  • Define Web personalization
  • Why a personalized Web would help
  • Details of online personalization

4
A Better Definition
  • A word from the experts.
  • Adaptable vs. Adaptive
  • Producers and Consumers-what does personalization
    mean to each (apps)
  • The details 2 phase personalized view

5
And the experts say
  • Any action that tailors the Web experience to a
    particular user, or a set of users. 1
  • The process of personalization includes gathering
    and storing information, analyzing that
    information, and based on that analysis,
    presenting a modified view to each visitor at the
    right time. 2
  • Process, not just a presentation.

6
Adaptable or Adaptive?
  • Adaptable Systems which allow the modification
    of certain parameters by the user.
  • Adaptive Systems which adapt themselves
    automatically to current user needs or perceived
    requirements, create an appropriate environment
    for the user, or modify a users experience. 3

7
Producers and Consumers
  • Producers
  • Marketing
  • Security
  • Usability
  • Consumers
  • Expectations
  • Efficiency
  • Selective Presentation

8
2 Phases of Personalization
  • Not collecting user input, where does the data
    come from?
  • Is data all we need?
  • Entire Process
  • Gathering storing information
  • Analyzing information
  • Present modified view

9
Offline Preparation
  • Collaborative Filtering 4
  • Web Content Mining Structure Mining 5
  • Web Usage Mining 6
  • Human Foraging Theory 7,8

10
Online Presentation
  • Site Map 9
  • Information Flow 10,11
  • Prefetching 12
  • Recommendation Engine 13

11
Summary
  • Defined personalization
  • Interest for producers and consumers.
  • Offline Online phases
  • Personalization is here to stay.
  • Machine learning and Intelligent Systems
  • Integrated Internet

12
References
  • 1 Bamshad Mobasher, Honghua Dai, Tao Luo,
    Yuqing Sun, Jiang Zhu. "Integrating Web Usage and
    Content Mining for More Effective
    Personalization," Proc. of the Intl. Conf. on
    ECommerce and Web Technologies (ECWeb). 2000.
  • 2 Honghua (Kathy) Dai, Bamshad Mobasher. "A
    Road map to More Effective Web Personalization
    Integrating Domain Knowledge with Web Usage
    Mining".
  • 3 Mike Perkowitz, Oren Etzioni. "Towards
    Adaptive Web Sites Conceptual Framework and Case
    Study," Computer Networks (Amsterdam,
    Netherlands 1999). 2001.
  • 4 J. L. Herlocker, J. A. Konstan, A. Borchers,
    and J. Riedl. "An algorithmic framework for
    performing collaborative filtering," In
    Proceedings of the 22nd annual international ACM
    SIGIR conference on Research and development in
    information retrieval, pages 230-237. 1999.
  • 5 R. Cooley, B. Mobasher, J. Srivastava. "Web
    Mining Information and Pattern Discovery on the
    World Wide Web," Proceedings of the 9th IEEE
    International Conference on Tools with Artificial
    Intelligence (ICTAI'97). 1997.
  • 6 Jaideep Srivastava, Robert Cooley, Mukund
    Deshpande, Pang-Ning Tan. "Web Usage Mining
    Discovery and Applications of Usage Patterns from
    Web Data," SIGKDD Explorations. 2000.
  • 7 Ed H. Chi, Peter Pirolli, Kim Chen, James
    Pitkow. "Using Information Scent to Model User
    Information Needs and Actions on the Web,"
    Proceedings of CHI. 2001.
  • 8 Peter Pirolli, Stuart K. Card. "Information
    Foraging". 1999.

13
References
  • 9 Fergus Toolan, Nicholas Kushmerick. Mining
    Web Logs for Personalized Site Maps. 2002.
  • 10 Barrett, R., Maglio, P. P., Kellem, D. C.
    "How to personalize the web, Proceedings of the
    ACM Conference on Human Factors in Computing
    Systems," (CHI '97), Atlanta, GA. 1997.
  • 11 P.P. Maglio and R. Barrett. "Intermediaries
    personalize information streams," Communications
    of the ACM, 43(8), pp. 96-101, 2000.
  • 12 Alexandros Nanopoulos, Dimitrios Katsaros,
    Yannis Manolopoulos. "A Data Mining Algorithm for
    Generalized Web Prefetching". 2002.
  • 13 Bamshad Mobasher, Robert Cooley, Jaideep
    Srivastava. "Automatic Personalization Based on
    Web Usage Mining," Communications of the ACM.
    1999.
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