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.

View at publisher


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:

0 citations in Scopus
Search Google Scholar™

Citation counts are sourced monthly from Scopus and Web of Science® citation databases.

These databases contain citations from different subsets of available publications and different time periods and thus the citation count from each is usually different. Some works are not in either database and no count is displayed. Scopus includes citations from articles published in 1996 onwards, and Web of Science® generally from 1980 onwards.

Citations counts from the Google Scholar™ indexing service can be viewed at the linked Google Scholar™ search.

Full-text downloads:

7 since deposited on 20 May 2016
7 in the past twelve months

Full-text downloads displays the total number of times this work’s files (e.g., a PDF) have been downloaded from QUT ePrints as well as the number of downloads in the previous 365 days. The count includes downloads for all files if a work has more than one.

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

Export: EndNote | Dublin Core | BibTeX

Repository Staff Only: item control page