The Science and Information (SAI) Organization
  • Home
  • About Us
  • Journals
  • Conferences
  • Contact Us

Publication Links

  • IJACSA
  • Author Guidelines
  • Publication Policies
  • Metadata Harvesting (OAI2)
  • Digital Archiving Policy
  • Promote your Publication

IJACSA

  • About the Journal
  • Call for Papers
  • Author Guidelines
  • Fees/ APC
  • Submit your Paper
  • Current Issue
  • Archives
  • Indexing
  • Editors
  • Reviewers
  • Apply as a Reviewer

IJARAI

  • About the Journal
  • Archives
  • Indexing & Archiving

Special Issues

  • Home
  • Archives
  • Proposals
  • Guest Editors

Future of Information and Communication Conference (FICC)

  • Home
  • Call for Papers
  • Submit your Paper/Poster
  • Register
  • Venue
  • Contact

Computing Conference

  • Home
  • Call for Papers
  • Submit your Paper/Poster
  • Register
  • Venue
  • Contact

Intelligent Systems Conference (IntelliSys)

  • Home
  • Call for Papers
  • Submit your Paper/Poster
  • Register
  • Venue
  • Contact

Future Technologies Conference (FTC)

  • Home
  • Call for Papers
  • Submit your Paper/Poster
  • Register
  • Venue
  • Contact
  • Home
  • Call for Papers
  • Indexing
  • Submit your Paper
  • Guidelines
  • Fees
  • Current Issue
  • Archives
  • Editors
  • Reviewers
  • Subscribe

DOI: 10.14569/IJACSA.2018.091102

A Method for Implementing Probabilistic Entity Resolution

Author 1: Awaad Alsarkhi
Author 2: John R. Talburt

PDF

International Journal of Advanced Computer Science and Applications(IJACSA), Volume 9 Issue 11, 2018.

  • Abstract and Keywords
  • How to Cite this Article
  • {} BibTeX Source

Abstract: Deterministic and probabilistic are two approaches to matching commonly used in Entity Resolution (ER) systems. While many users are familiar with writing and using Boolean rules for deterministic matching, fewer are as familiar with the scoring rule configuration used to support probabilistic matching. This paper describes a method using deterministic matching to “bootstrap” probabilistic matching. It also examines the effectiveness three commonly used strategies to mitigate the effect of missing values when using probabilistic matching. The results based on experiment using different sets of synthetically generated data processed using the OYSTER open source entity resolution system.

Keywords: Entity resolution; probabilistic matching; deterministic matching; boolean rules; scoring rule; missing values

Awaad Alsarkhi and John R. Talburt, “A Method for Implementing Probabilistic Entity Resolution” International Journal of Advanced Computer Science and Applications(IJACSA), 9(11), 2018. http://dx.doi.org/10.14569/IJACSA.2018.091102

@article{Alsarkhi2018,
title = {A Method for Implementing Probabilistic Entity Resolution},
journal = {International Journal of Advanced Computer Science and Applications},
doi = {10.14569/IJACSA.2018.091102},
url = {http://dx.doi.org/10.14569/IJACSA.2018.091102},
year = {2018},
publisher = {The Science and Information Organization},
volume = {9},
number = {11},
author = {Awaad Alsarkhi and John R. Talburt}
}



Copyright Statement: This is an open access article licensed under a Creative Commons Attribution 4.0 International License, which permits unrestricted use, distribution, and reproduction in any medium, even commercially as long as the original work is properly cited.

IJACSA

Upcoming Conferences

Future of Information and Communication Conference (FICC) 2024

4-5 April 2024

  • Berlin, Germany

Computing Conference 2024

11-12 July 2024

  • London, United Kingdom

IntelliSys 2023

7-8 September 2023

  • Amsterdam, The Netherlands

Future Technologies Conference (FTC) 2023

2-3 November 2023

  • San Francisco, United States
The Science and Information (SAI) Organization
BACK TO TOP

Computer Science Journal

  • About the Journal
  • Call for Papers
  • Submit Paper
  • Indexing

Our Conferences

  • Computing Conference
  • Intelligent Systems Conference
  • Future Technologies Conference
  • Communication Conference

Help & Support

  • Contact Us
  • About Us
  • Terms and Conditions
  • Privacy Policy

© The Science and Information (SAI) Organization Limited. All rights reserved. Registered in England and Wales. Company Number 8933205. thesai.org