Yafang Wang
ABSTRACT
We demonstrate the YaLi browser plug-in which discovers named entities in Web pages and provides background knowledge about them. The plug-in is implemented with two purposes. From a user perspective, it enriches the browsing experience with entities, helping users with their information needs. From the research perspective, we aim to improve the methods that are used for named entity recognition and disambiguation (NERD) by leveraging the plug-in as an implicit crowdsourcing platform. YaLi tracks the system's errors and the users' corrections, and also gathers implicit training data for improving NERD accuracy.
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Digital Library
- M. J. Franklin, D. Kossmann, T. Kraska, S. Ramesh, R. Xin. CrowdDB: Answering queries with crowdsourcing. SIGMOD, 2011. Google ScholarDigital Library
- J. Hoffart, et al.. Robust disambiguation of named entities in text. EMNLP, 2011. Google ScholarDigital Library
- V. I. Spitkovsky, A. X. Chang. A cross-lingual dictionary for English Wikipedia concepts. LREC, 2012.Google Scholar
- J. Wang, T. Kraska, M. J. Franklin, J. Feng. CrowdER: Crowdsourcing entity resolution. VLDB, 2012. Google ScholarDigital Library
- T. Yan, V. Kumar, D. Ganesan. CrowdSearch: Exploiting crowds for accurate real-time image search on mobile phones. In MobiSys, 2010. Google ScholarDigital Library
Index Terms
- YaLi: a crowdsourcing plug-in for NERD
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