TUbilio (Technical University of Darmstadt) · 2011 · 10 citations · 5 references
This paper describes UKP’s participation in the cross-lingual link discovery (CLLD) task at NTCIR-9. The given task is to find valid anchor texts from a new English Wikipedia page and retrieve the corresponding target Wiki pages in Chinese, Japanese, and Korean languages. We have developed a CLLD framework consisting of anchor selection, anchor ranking, anchor translation, and target discovery subtasks, and discovered anchor texts from English Wikipedia pages and their corresponding targets in Chinese, Japanese, and Korean languages. For anchor selection, anchor ranking, and target discovery, we have largely utilized the state-ofthe-art monolingual approaches. For anchor translation, we utilize a translation resource constructed from Wikipedia itself in addition to exploring a number of methods that have been widely used for short phrase translation. Our formal runs performed very competitively compared to other participants’ systems. Our system came first in the English-2-Chinese and the English-2-Korean F2F with manual assessment and A2F with Wikipedia ground truth assessment evaluations using Mean-Average-Precision (MAP) measure.
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Learning to link with wikipedia
David Milne, Ian H. Witten · 2008 · 1.3K citations
Natural Language Processing, Engineering, Information Retrieval +15
Rada Mihalcea, Andras Csomai · 2007 · 922 citations
Natural Language Processing, Online Encyclopedia, Engineering +15
Link Discovery: A Comprehensive Analysis
Nicolai Erbs, Torsten Zesch, Iryna Gurevych · 2011 · 18 citations