Identification of Duplicate News Stories in Web Pages

Abstract

Identifying near duplicate documents is a challenge often faced in the field of information discovery. Unfortunately many algorithms that find near duplicate pairs of plain text documents perform poorly when used on web pages, where metadata and other extraneous information make that process much more difficult. If the content of the page (e.g., the body of a news article) can be extracted from the page, then the accuracy of the duplicate detection algorithms is greatly increased. Using machine learning techniques to identify the content portion of web pages, we achieve accuracy that is nearly identical to plain text and significantly better than simple heuristic approaches to content extraction. We performed these experiments on a small, but fully annotated corpus.

Open PDF

Document Details

Document Type
Technical Report
Publication Date
Jan 01, 2008
Accession Number
AD1107117

Entities

People

  • Ben Wellner
  • John Gibson
  • Susan Lubar

Organizations

  • MITRE Corporation

Tags

Communities of Interest

  • Autonomy

DTIC Thesaurus Topics

  • Accuracy
  • Algorithms
  • Computational Linguistics
  • Computational Science
  • Computers
  • Data Management
  • Data Set
  • Data Sets
  • Detection
  • Digital Data
  • Fingerprints
  • Identification
  • Internet
  • Language
  • Linguistics
  • Machine Learning
  • Natural Language Computing
  • Natural Language Processing
  • Natural Languages
  • New York
  • Precision
  • Recognition
  • Standards
  • Websites
  • World Wide Web

Fields of Study

  • Computer science

Readers

  • Agent-Based Social Robotics and Mobile-Assisted Learning in Virtual Environments.
  • Business Analytics
  • Mathematics or Statistics

Technology Areas

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