Discovering and ranking new links for linked data supplier

Nansu Zong, Sungkwon Yang, Hyun Namgoong, Hong Gee Kim

Research output: Chapter in Book/Report/Conference proceedingConference contribution

Abstract

For new data supplier who wants to join the web of data club, it's difficult to find new links between local repository and data sets in the web of data to make local data well-connected or harmonize with other data. The purpose of this research is not for finding similar entities but discovering new potential link for helping users have more choice for using multiple links instead of only using "owl:sameAs". The approach use information retrieval technique index the data sets and Page Rank and graph theory analyze RDF document to filter links. We implemented our method using Dbpedia data sets and two open ontologies, the results showed our approach can discover new links with highly accuracy.

Original languageEnglish (US)
Title of host publicationThe Semantic Web - Joint International Semantic Technology Conference, JIST 2011, Proceedings
Pages358-365
Number of pages8
DOIs
StatePublished - 2012
EventJoint International Semantic Technology Conference, JIST 2011 - Hangzhou, China
Duration: Dec 4 2011Dec 7 2011

Publication series

NameLecture Notes in Computer Science (including subseries Lecture Notes in Artificial Intelligence and Lecture Notes in Bioinformatics)
Volume7185 LNCS
ISSN (Print)0302-9743
ISSN (Electronic)1611-3349

Other

OtherJoint International Semantic Technology Conference, JIST 2011
Country/TerritoryChina
CityHangzhou
Period12/4/1112/7/11

Keywords

  • Entity Ranking
  • Link Discovering
  • Linked Data

ASJC Scopus subject areas

  • Theoretical Computer Science
  • Computer Science(all)

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