|Cross-lingual knowledge linking across wiki knowledge bases|
|Author(s)||Wang Z., Li J., Wang Z., Tang J.|
|Published in||WWW'12 - Proceedings of the 21st Annual Conference on World Wide Web|
|Keyword(s)||Cross-lingual, Knowledge linking, Knowledge sharing, Wiki knowledge base (Extra: Critical issues, Cross-lingual, Data sets, Factor graphs, High precision, Knowledge base, Knowledge basis, Knowledge linking, Knowledge-sharing, Wikipedia, Knowledge based systems, Websites)|
|Article||BASE, CiteSeerX, Google Scholar|
|Web||Ask, Bing, Google (PDF), Yahoo!|
|Download and mirrors|
|Local copy||Not available|
|Remote mirror(s)||Not available|
|Export and share|
|BibTeX, CSV, RDF, JSON|
|Browse properties · List of conference papers|
Cross-lingual knowledge linking across wiki knowledge bases is a 2012 conference paper written in English by Wang Z., Li J., Wang Z., Tang J. and published in WWW'12 - Proceedings of the 21st Annual Conference on World Wide Web.
Wikipedia becomes one of the largest knowledge bases on the Web. It has attracted 513 million page views per day in January 2012. However, one critical issue for Wikipedia is that articles in different language are very unbalanced. For example, the number of articles on Wikipedia in English has reached 3.8 million, while the number of Chinese articles is still less than half million and there are only 217 thousand cross-lingual links between articles of the two languages. On the other hand, there are more than 3.9 million Chinese Wiki articles on Baidu Baike and Hudong.com, two popular encyclopedias in Chinese. One important question is how to link the knowledge entries distributed in different knowledge bases. This will immensely enrich the information in the online knowledge bases and benefit many applications. In this paper, we study the problem of cross-lingual knowledge linking and present a linkage factor graph model. Features are defined according to some interesting observations. Experiments on the Wikipedia data set show that our approach can achieve a high precision of 85.8% with a recall of 88.1%. The approach found 202,141 new cross-lingual links between English Wikipedia and Baidu Baike.
- This section requires expansion. Please, help!
Probably, this publication is cited by others, but there are no articles available for them in WikiPapers. Cited 9 time(s)