Overview of the NTCIR-9 crosslink task : cross-lingual link discovery
Tang, Ling-Xiang, Geva, Shlomo, Trotman, Andrew, Xu, Yue, & Itakura, Kelly (2011) Overview of the NTCIR-9 crosslink task : cross-lingual link discovery. In Kando, Noriko, Ishikawa, Daisuke, & Sugimoto, Miho (Eds.) Proceedings of the 9th NTCIR Workshop Meeting on Evaluation of Information Access Technologies: Information Retreival, Question Answering and Cross-Lingual Information Access, National Institute of Informatics, National Center of Sciences, Tokyo, pp. 437-463.
This paper presents an overview of NTCIR-9 Cross-lingual Link Discovery (Crosslink) task. The overview includes: the
motivation of cross-lingual link discovery; the Crosslink task definition; the run submission specification; the assessment and evaluation framework; the evaluation metrics; and the evaluation results of submitted runs.
Cross-lingual link discovery (CLLD) is a way of automatically finding potential links between documents in different languages. The goal of this task is to create a reusable resource for evaluating automated CLLD approaches. The results of this research can be used in building and refining systems for automated link discovery. The task is focused on linking between English source documents and Chinese, Korean, and Japanese target documents.
Citation countsare sourced monthly fromand 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 theindexing service can be viewed at the linked Google Scholar™ search.
|Item Type:||Conference Paper|
|Keywords:||Wikipedia, Cross-lingual link discovery, Anchor identification, Link recommendation, Validation tool, Assessment tool, Evaluation tool, Evaluation metrics|
|Subjects:||Australian and New Zealand Standard Research Classification > INFORMATION AND COMPUTING SCIENCES (080000) > ARTIFICIAL INTELLIGENCE AND IMAGE PROCESSING (080100) > Natural Language Processing (080107)|
Australian and New Zealand Standard Research Classification > INFORMATION AND COMPUTING SCIENCES (080000) > COMPUTER SOFTWARE (080300) > Open Software (080306)
|Divisions:||Current > Schools > School of Electrical Engineering & Computer Science|
Current > QUT Faculties and Divisions > Science & Engineering Faculty
|Copyright Owner:||© 2011 National Institute of Informatics|
|Deposited On:||14 Mar 2012 08:02|
|Last Modified:||14 Mar 2012 08:02|
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