How To Clean Domain_6 Data

---

SIAM Epidemiology Collection
In response to the outbreak of the novel coronavirus SARS-CoV-2 and the associated disease COVID-19, SIAM has made the following collection freely available. We hope this content on epidemiology, disease modeling, pandemics and vaccines will help in the rapid fight against this global problem. Click on title above or here to access this collection.

---

• Keyword
• Citation
• DOI/ISSN
• Advanced Search

• Sign in
• Help
• View Cart

• Home
• Journals
  • Locus
  • Multiscale Modeling & Simulation
    • Browse MMS
  • SIAM J. on Applied Algebra and Geometry
    • Browse SIAGA
  • SIAM J. on Applied Dynamical Systems
    • Browse SIADS
  • SIAM J. on Applied Mathematics
    • Browse SIAP
  • SIAM J. on Computing
    • Browse SICOMP
  • SIAM J. on Control and Optimization
    • Browse SICON
  • SIAM J. on Discrete Mathematics
    • Browse SIDMA
  • SIAM J. on Financial Mathematics
    • Browse SIFIN
  • SIAM J. on Imaging Sciences
    • Browse SIIMS
  • SIAM J. on Mathematical Analysis
    • Browse SIMA
  • SIAM J. on Mathematics of Data Science
    • Browse SIMODS
  • SIAM J. on Matrix Analysis and Applications
    • Browse SIMAX
  • SIAM J. on Numerical Analysis
    • Browse SINUM
  • SIAM J. on Optimization
    • Browse SIOPT
  • SIAM J. on Scientific Computing
    • Browse SISC
  • SIAM/ASA J. on Uncertainty Quantification
    • Browse JUQ
  • SIAM Review
    • Browse SIREV
  • Theory of Probability & Its Applications
    • Browse TVP
  • FAQ
• E-books
  • Browse e-books
  • Series Descriptions
  • Book Program
  • MARC Records
  • FAQ
• Proceedings
• For Authors
  • Journal Author Submissions
  • Book Author Submissions
• Subscriptions
  • Journal Subscription
  • Journal Pricing
  • Journal Subscription Agreement
  • E-book Subscription
  • E-book Purchase
  • E-book Licensing Agreement
• Interactive Features
  • Journal / E-book / Proceedings TOC Alerts
  • Facebook
  • Twitter
  • YouTube
• Journal Citations
• Contact Us
  • Feedback
  • SIAM Website

• Home >
• Proceedings >
• Proceedings of the 2005 SIAM International Conference on Data Mining (SDM) >
• 10.1137/1.9781611972757.24

Manage this Paper

Add to my favorites

Download Citations

Track Citations

Notify Me!

E-mail Alerts

RSS Feeds

Proceedings of the 2005 SIAM International Conference on Data Mining (SDM)

< Previous Chapter

Next Chapter >

Table of Contents

• Abstract
• PDF

Exploiting relationships for domain-independent data cleaning*†

Dmitri V. Kalashnikov, Sharad Mehrotra and Zhaoqi Chen

This Paper Appears in

Title Information

Published: 2005

ISBN: 978-0-89871-593-4

eISBN: 978-1-61197-275-7

Book Code: PR119

Pages: 12

*RelDC project (http://www.ics.uci.edu/∼dvk/RelDC)

†This work was supported in part by NSF grants 0331707, 0331690, and IRI-9703120.

Abstract

In this paper we address the problem of reference disambiguation. Specifically, we consider a situation where entities in the database are referred to using descriptions (e.g., a set of instantiated attributes). The objective of reference disambiguation is to identify the unique entity to which each description corresponds. The key difference between the approach we propose (called RelDC) and the traditional techniques is that RelDC analyzes not only object features but also inter-object relationships to improve the disambiguation quality. Our extensive experiments over two real datasets and also over synthetic datasets show that analysis of relationships significantly improves quality of the result.

Permalink: https://doi.org/10.1137/1.9781611972757.24

© 2021 SIAM By using SIAM Publications Online you agree to abide by the Terms and Conditions of Use.
Banner art adapted from a figure by Hinke M. Osinga and Bernd Krauskopf (University of Auckland, NZ).
Powered by Atypon® Literatum

How To Clean Domain_6 Data

Source: https://epubs.siam.org/doi/10.1137/1.9781611972757.24

Posted by: perrymerhade80.blogspot.com

Share this post