WebWatcher: Machine Learning and Hypertext

reportActive / Technical Report | Accession Number: ADA635877 | Open PDF

Abstract:

This paper describes the first implementation of WebWatcher, a Learning Apprentice for the World Wide Web. We also explore the possibility of extracting information from the structure of hypertext. We introduce an algorithm which identifies pages that are related to a given page using only hypertext structure. We motivate the algorithm by using the Minimum Description Length principle.

Author(s):
Joachims, Thorsten ; Mitchell, Tom ; Freitag, Dayne ; Armstrong, Robert
Author Organization(s):
CARNEGIE-MELLON UNIV PITTSBURGH PA SCHOOL OF COMPUTER SCIENCE
Supplementary Note:
DOI: 10.21236/ADA635877
Pagination:
0006

Security Markings

DOCUMENT & CONTEXTUAL SUMMARY

Distribution:
Approved For Public Release
Distribution Statement:
Approved For Public Release; Distribution Is Unlimited.

RECORD

Collection: TR
Identifying Numbers
Contract/Grant Number(s):
F33615-93-1-1330
Monitor Series:
ARPA
 Subject Terms
Joint Capability Areas:
JCA_5_Command and Control; JCA_5.2.2_Develop Knowledge and Situational Awareness; JCA_5.2_Understand; JCA_5.3_Planning; JCA_1.2_Force Preparation; JCA_1_Force Support; JCA_8_Building Partnerships
Modernization Areas:
Autonomy
Communities of Interest:
Autonomy
Descriptor(s):
*ALGORITHMS, *HYPERTEXT, *LEARNING MACHINES, INTERNET
Field(s)/Group(s):
Numerical Mathematics, Computer Programming and Software, Cybernetics
Keyword(s):
WEBWATCHER, MACHINE LEARNING, WWW(WORLD WIDE WEB), MDL(MINIMUM DESCRIPTION LENGTH)
Report Date:
1995 May 29
Creation Date:
2016 Aug 22