Named Entity Recognition for IDEAL

This project explored how to apply Named Entity Recognition to large Twitter and web page datasets to extract useful entities such as people, organization, location, and date. In addition, this NER utility has been scaled to the MapReduce framework on the Hadoop cluster. A schema and software allow this to be integrated with IDEAL.

[1]  Lawrence R. Rabiner,et al.  A tutorial on hidden Markov models and selected applications in speech recognition , 1989, Proc. IEEE.

[2]  Satoshi Sekine,et al.  A survey of named entity recognition and classification , 2007 .

[3]  Jeff Morris,et al.  Computational Linguistics Hurricane Group , 2014 .

[4]  Lorraine K. Tanabe,et al.  GENETAG: a tagged corpus for gene/protein named entity recognition , 2005, BMC Bioinformatics.

[5]  Ralph Grishman,et al.  Message Understanding Conference- 6: A Brief History , 1996, COLING.

[6]  Jian Su,et al.  Named Entity Recognition using an HMM-based Chunk Tagger , 2002, ACL.

[7]  Huang Wei,et al.  Unsupervised Event Extraction from News and Twitter , 2014 .

[8]  David Nadeau,et al.  Semi-supervised named entity recognition: learning to recognize 100 entity types with little supervision , 2007 .

[9]  David Keimig,et al.  Natural Language Processing: Generating a Summary of Flood Disasters , 2014 .

[10]  Changki Lee,et al.  Fine-Grained Named Entity Recognition Using Conditional Random Fields for Question Answering , 2006, AIRS.

[11]  Dan Roth,et al.  Design Challenges and Misconceptions in Named Entity Recognition , 2009, CoNLL.

[12]  Dekang Lin,et al.  Phrase Clustering for Discriminative Learning , 2009, ACL.

[13]  Dekang Lin,et al.  Proceedings of the 49th Annual Meeting of the Association for Computational Linguistics: Human Language Technologies - Volume 1 , 2011 .

[14]  Christopher D. Manning,et al.  Incorporating Non-local Information into Information Extraction Systems by Gibbs Sampling , 2005, ACL.