AGDISTIS-agnostic disambiguation of named entities using linked open data
Research output: Contributions to collected editions/works › Article in conference proceedings › Research › peer-review
Authors
Over the last decades, several billion Web pages have been made available on the Web. The ongoing transition from the current Web of unstructured data to the Data Web yet requires scalable and accurate approaches for the extraction of structured data in RDF (Resource Description Framework) from these websites. One of the key steps towards extracting RDF from text is the disambiguation of named entities. We address this issue by presenting AGDISTIS, a novel knowledge-base-agnostic approach for named entity disambiguation. Our approach combines the Hypertext-Induced Topic Search (HITS) algorithm with label expansion strategies and string similarity measures. Based on this combination, AGDISTIS can efficiently detect the correct URIs for a given set of named entities within an input text.
| Original language | English |
|---|---|
| Title of host publication | ECAI 2014 - 21st European Conference on Artificial Intelligence, Including Prestigious Applications of Intelligent Systems, PAIS 2014, Proceedings |
| Editors | Torsten Schaub, Gerhard Friedrich, Barry O'Sullivan |
| Number of pages | 2 |
| Publisher | IOS Press BV |
| Publication date | 2014 |
| Pages | 1113-1114 |
| ISBN (print) | 978-1-61499-418-3 |
| ISBN (electronic) | 978-1-61499-419-0 |
| DOIs | |
| Publication status | Published - 2014 |
| Externally published | Yes |
| Event | 21st European Conference on Artificial Intelligence, ECAI 2014 - Prague, Czech Republic Duration: 18.08.2014 → 22.08.2014 Conference number: 21 http://www.ecai2014.org/ |
Bibliographical note
Publisher Copyright:
© 2014 The Authors and IOS Press.
- Informatics
- Business informatics