A Short Survey of Linked Data Ranking

dc.contributor.author	YUMUŞAK, Semih
dc.contributor.author	DOĞDU, Erdoğan
dc.contributor.author	KODAZ, Halife
dc.date.accessioned	2020-08-07T13:02:20Z
dc.date.available	2020-08-07T13:02:20Z
dc.date.issued	2014
dc.identifier	10.1145/2638404.2638523
dc.identifier.issn	9781450329231 (ISBN)
dc.identifier.uri	http://hdl.handle.net/20.500.12498/3146
dc.description.abstract	Linked data systems are still far from maturity. Hence, the basic principles are still open for discussion. In our study on building a novel linked data search engine, we have surveyed fundamental methods of internet search technologies in the context of linked data crawling, indexing, ranking, and monitoring. The scope of this ranking survey covers linked data related statistical ranking, database ranking, document level ranking, and Web ranking techniques. In order to classify the linked data ranking methods, we identified a number of categories. These categories are ontology ranking, RDF ranking, graph ranking, entity ranking, document/domain ranking. At the end of the survey, we have listed the ranking techniques based on the well-known PageRank algorithm. Copyright 2014 ACM.
dc.language.iso	English
dc.publisher	Association for Computing Machinery, Inc
dc.source	2014 ACM Southeast Regional Conference, ACM SE 2014
dc.subject	Ranking
dc.subject	Data Processing
dc.subject	Information Retrieval
dc.title	A Short Survey of Linked Data Ranking
dc.type	Konferans Bildirisi