Using Bayesian decision for ontology mapping
Web Semantics: Science, Services and Agents on the World Wide Web
Wikify!: linking documents to encyclopedic knowledge
Proceedings of the sixteenth ACM conference on Conference on information and knowledge management
Learning to link with wikipedia
Proceedings of the 17th ACM conference on Information and knowledge management
Enriching Multilingual Language Resources by Discovering Missing Cross-Language Links in Wikipedia
WI-IAT '08 Proceedings of the 2008 IEEE/WIC/ACM International Conference on Web Intelligence and Intelligent Agent Technology - Volume 01
Collective annotation of Wikipedia entities in web text
Proceedings of the 15th ACM SIGKDD international conference on Knowledge discovery and data mining
RiMOM: A Dynamic Multistrategy Ontology Alignment Framework
IEEE Transactions on Knowledge and Data Engineering
DBpedia - A crystallization point for the Web of Data
Web Semantics: Science, Services and Agents on the World Wide Web
A Wikipedia-based multilingual retrieval model
ECIR'08 Proceedings of the IR research, 30th European conference on Advances in information retrieval
MENTA: inducing multilingual taxonomies from wikipedia
CIKM '10 Proceedings of the 19th ACM international conference on Information and knowledge management
Using pseudo feedback to improve cross-lingual ontology mapping
ESWC'11 Proceedings of the 8th extended semantic web conference on The semantic web: research and applications - Volume Part I
Collective entity linking in web text: a graph-based method
Proceedings of the 34th international ACM SIGIR conference on Research and development in Information Retrieval
A machine learning approach to multilingual and cross-lingual ontology matching
ISWC'11 Proceedings of the 10th international conference on The semantic web - Volume Part I
LINDEN: linking named entities with knowledge base via semantic knowledge
Proceedings of the 21st international conference on World Wide Web
Cross-lingual knowledge linking across wiki knowledge bases
Proceedings of the 21st international conference on World Wide Web
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Automatically discovering cross-lingual links (CLs) between wikis can largely enrich the cross-lingual knowledge and facilitate knowledge sharing across different languages. In most existing approaches for cross-lingual knowledge linking, the seed CLs and the inner link structures are two important factors for finding new CLs. When there are insufficient seed CLs and inner links, discovering new CLs becomes a challenging problem. In this paper, we propose an approach that boosts cross-lingual knowledge linking by concept annotation. Given a small number of seed CLs and inner links, our approach first enriches the inner links in wikis by using concept annotation method, and then predicts new CLs with a regression-based learning model. These two steps mutually reinforce each other, and are executed iteratively to find as many CLs as possible. Experimental results on the English and Chinese Wikipedia data show that the concept annotation can effectively improve the quantity and quality of predicted CLs. With 50,000 seed CLs and 30% of the original inner links in Wikipedia, our approach discovered 171,393 more CLs in four runs when using concept annotation.