Discovering and Ranking New Links for Linked Data Supplier

Autor:	Hyun Namgoong, Hong-Gee Kim, Sung-Kwon Yang, Nansu Zong
Rok vydání:	2012
Předmět:	World Wide Web Index (publishing) Computer science Graph theory computer.file_format Linked data RDF Filter (higher-order function) Page rank Link (knot theory) computer Ranking (information retrieval)
Zdroj:	The Semantic Web ISBN: 9783642299223 JIST
DOI:	10.1007/978-3-642-29923-0_25
Popis:	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.
Databáze:	OpenAIRE
Externí odkaz:	https://explore.openaire.eu/search/publication?articleId=doi_________::98a97d6ffaad0156914a183a3159d144 https://doi.org/10.1007/978-3-642-29923-0_25 Zobrazit plný text záznamu