%0 Journal Article %1 6823700 %A Shen, W. %A Wang, J. %A Han, J. %D 2015 %J Knowledge and Data Engineering, IEEE Transactions on %K disambiguation linking phdproposal survey %N 2 %P 443-460 %R 10.1109/TKDE.2014.2327028 %T Entity Linking with a Knowledge Base: Issues, Techniques, and Solutions %U http://ieeexplore.ieee.org/xpls/abs_all.jsp?arnumber=6823700 %V 27 %X The large number of potential applications from bridging web data with knowledge bases have led to an increase in the entity linking research. Entity linking is the task to link entity mentions in text with their corresponding entities in a knowledge base. Potential applications include information extraction, information retrieval, and knowledge base population. However, this task is challenging due to name variations and entity ambiguity. In this survey, we present a thorough overview and analysis of the main approaches to entity linking, and discuss various applications, the evaluation of entity linking systems, and future directions.

@article{6823700, abstract = {The large number of potential applications from bridging web data with knowledge bases have led to an increase in the entity linking research. Entity linking is the task to link entity mentions in text with their corresponding entities in a knowledge base. Potential applications include information extraction, information retrieval, and knowledge base population. However, this task is challenging due to name variations and entity ambiguity. In this survey, we present a thorough overview and analysis of the main approaches to entity linking, and discuss various applications, the evaluation of entity linking systems, and future directions.}, added-at = {2015-01-06T14:18:52.000+0100}, author = {Shen, W. and Wang, J. and Han, J.}, biburl = {https://www.bibsonomy.org/bibtex/24feb39e3738869500cee4c743ff6f888/asmelash}, description = {IEEE Xplore Abstract - Entity Linking with a Knowledge Base: Issues, Techniques, and Solutions}, doi = {10.1109/TKDE.2014.2327028}, interhash = {796897f2a8898f025fd221a29190370c}, intrahash = {4feb39e3738869500cee4c743ff6f888}, issn = {1041-4347}, journal = {Knowledge and Data Engineering, IEEE Transactions on}, keywords = {disambiguation linking phdproposal survey}, month = feb, number = 2, pages = {443-460}, timestamp = {2015-01-06T14:21:28.000+0100}, title = {Entity Linking with a Knowledge Base: Issues, Techniques, and Solutions}, url = {http://ieeexplore.ieee.org/xpls/abs_all.jsp?arnumber=6823700}, volume = 27, year = 2015 }