AGDISTIS - agnostic disambiguation of named entities using linked open data

• DOI: 10.3233/978-1-61499-419-0-1113
• Publication Date: 2014-08-18
• Authors: Ricardo Usbeck; Axel-Cyrille Ngon...; Michael Röder; Dániel Gerber; Sandro Athaíde Co...; Sören Auer; Andreas Both
• Keywords: Linked Data; Unstructured data; Entity linking

Over the last decades, several billion Web pages have been made available on Web. The ongoing transition from current of unstructured data to Data yet requires scalable and accurate approaches for extraction structured in RDF (Resource Description Framework) these websites. One key steps towards extracting text is disambiguation named entities. We address this issue by presenting AGDISTIS, a novel knowledge-base-agnostic approach entity disambiguation. Our combines Hypertext-Induced Topic Search (HITS) algorithm with label expansion strategies string similarity measures. Based combination, AGDISTIS can efficiently detect correct URIs given set entities within an input text.