A short survey of linked data ranking

Semih Yumusak, Erdogan Dogdu, H. Kodaz
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引用次数: 8

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.
链接数据排名的简短调查
关联数据系统还远未成熟。因此,基本原则仍有待讨论。在我们构建一个新的关联数据搜索引擎的研究中,我们调查了在关联数据抓取、索引、排名和监控的背景下互联网搜索技术的基本方法。这个排名调查的范围包括与链接数据相关的统计排名、数据库排名、文档级别排名和Web排名技术。为了对关联数据排序方法进行分类,我们确定了一些类别。这些分类包括本体排序、RDF排序、图排序、实体排序、文档/领域排序。在调查的最后,我们列出了基于众所周知的PageRank算法的排名技术。
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