WebWatcher: A Learning Apprentice for the World Wide Web

Abstract

We describe an information seeking assistant for the world wide web. This agent, called WebWatcher, interactively helps users locate desired information by employing learned knowledge about which hyperlinks are likely to lead to the target information. Our primary focus to date has been on two issues: (1) organizing WebWatcher to provide interactive advice to Mosaic users while logging their successful and unsuccessful searches as training data, and (2) incorporating machine learning methods to automatically acquire knowledge for selecting an appropriate hyperlink given the current web page viewed by the user and the user's information goal. We describe the initial design of WebWatcher, and the results of our preliminary learning experiments

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Document Details

Document Type
Technical Report
Publication Date
Feb 01, 1995
Accession Number
ADA640219

Entities

People

  • Dayne Freitag
  • Robert Armstrong
  • Thorsten Joachims
  • Tom M. Mitchell

Organizations

  • Carnegie Mellon University

Tags

Communities of Interest

  • Autonomy

DTIC Thesaurus Topics

  • Abstracts
  • Accuracy
  • Artificial Intelligence
  • Case Studies
  • Coding
  • Computer Science
  • Data Science
  • Information Retrieval
  • Information Science
  • Language
  • Learning
  • Machine Learning
  • Networks
  • Probability
  • Training
  • Universities
  • World Wide Web

Fields of Study

  • Computer science

Readers

  • Agent-Based Social Robotics and Mobile-Assisted Learning in Virtual Environments.
  • Nuclear and Radiation Engineering.
  • Systems Analysis and Design

Technology Areas

  • AI & ML
  • AI & ML - Information Retrieval
  • AI & ML - Neural Networks