Oyster: A tool for fine-grained ontological annotations in free-text

Tayebikhorami, Hamed, Metke-Jimenez, Alejandro, Nguyen, Anthony, & Zuccon, Guido (2015) Oyster: A tool for fine-grained ontological annotations in free-text. In Information Retrieval Technology: 11th Asia Information Retrieval Societies Conference, AIRS 2015, Brisbane, QLD, Australia, December 2-4, 2015. Proceedings, Springer International Publishing, Brisbane, Qld, pp. 440-446.

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Abstract

Oyster is a web-based annotation tool that allows users to annotate free-text with respect to concepts defined in formal knowledge resources such as large domain ontologies. The tool has been explicitly designed to provide (manual and automatic) search functionalities to identify the best concept entities to be used for annotation. In addition, Oyster supports features such as annotations that span across non-adjacent tokens, multiple annotations per token, the identification of entity relationships and a user-friendly visualisation of the annotation including the use of filtering based on annotation types. Oyster is highly configurable and can be expanded to support a variety of knowledge resources. The tool can support a wide range of tasks involving human annotation, including named-entity extraction, relationship extraction, annotation correction and refinement.

Impact and interest:

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ID Code: 95673
Item Type: Conference Paper
Refereed: Yes
Additional Information: Volume 9460 of the series Lecture Notes in Computer Science
DOI: 10.1007/978-3-319-28940-3_39
ISBN: 9783319289397
ISSN: 0302-9743
Subjects: Australian and New Zealand Standard Research Classification > INFORMATION AND COMPUTING SCIENCES (080000) > LIBRARY AND INFORMATION STUDIES (080700) > Information Retrieval and Web Search (080704)
Divisions: Current > Schools > School of Electrical Engineering & Computer Science
Current > QUT Faculties and Divisions > Science & Engineering Faculty
Copyright Owner: Copyright 2015 Springer International Publishing Switzerland
Copyright Statement: The final publication is available at Springer via http://dx.doi.org/10.1007/978-3-319-28940-3_39
Deposited On: 20 May 2016 05:16
Last Modified: 31 Jan 2017 17:20

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