References

Bikel, D.M., R. Schwartz and R.M. Weischedel, 1999. An algorithm that learns whats in a name. Mach. Learn., 34: 211-231.
CrossRef  |  Direct Link  |  

Biswas, P., A. Sharan and A. Kumar, 2015. AGNER: Entity tagger in agriculture domain. Proceedings of the 2015 2nd International Conference on Computing for Sustainable Global Development (INDIACom), March 11-13, 2015, IEEE, New Delhi, India, ISBN: 978-9-3805-4415-1, pp: 1134-1138.

Borthwick, A., 1999. A maximum entropy approach to named entity recognition. Ph.D Thesis, New York University, New York, USA. http://citeseerx.ist.psu.edu/viewdoc/download?doi=10.1.1.641.2654&rep=rep1&type=pdf

Califf, M.E. and R.J. Mooney, 2003. Bottom-up relational learning of pattern matching rules for information extraction. J. Mach. Learn. Res., 4: 177-210.
Direct Link  |  

Carreras, X., L. Marquez and L. Padro, 2002. Named entity extraction using adaboost. Proc. Conf. Nat. Lang. Learn., 20: 1-4.
CrossRef  |  Direct Link  |  

Coates, S.S., 1992. The analysis and acquisition of proper names for the understanding of free text. Comput. Humanities, 26: 441-456.
CrossRef  |  Direct Link  |  

Curran, J.R. and S. Clark, 2003. Language independent NER using a maximum entropy tagger. Proceedings of the Seventh Conference on Natural Language Learning, May 31-June 1, 2003, ACM, Stroudsburg, Pennsylvania, USA., pp: 164-167.

Derczynski, L., D. Maynard, G. Rizzo, V.M. Erp and G. Gorrell et al., 2015. Analysis of named entity recognition and linking for tweets. Inf. Process. Manage., 51: 32-49.
Direct Link  |  

Etzioni, O., M. Cafarella, D. Downey, A.M. Popescu and T. Shaked et al., 2005. Unsupervised named-entity extraction from the web: An experimental study. Artif. Intell., 165: 91-134.
CrossRef  |  Direct Link  |  

Finkel, J.R., T. Grenager and C. Manning, 2005. Incorporating non-local information into information extraction systems by gibbs sampling. Proceedings of the 43rd Annual Meeting on Association for Computational Linguistics, June 25-30, 2005, ACM, Stroudsburg, Pennsylvania, USA, pp: 363-370.

Fog Computing World, 2014. Internet of things to generate zettabytes of data by 2018. Fog Computing Publishing, Palo Alto, California. http://www.fogcomputingworld.com/topics/fog-computing/articles/393474-internet-things-generate-zettabytes-data-2018.htm

Freitag, D. and N. Kushmerick, 2000. Boosted wrapper induction. Proceedings of the 17th National Conference on Artificial Intelligence, July 31-August 2, 2000, AAAI Press/The MIT Press, Austin, TX., pp: 577-583.

Ge, Y., H. Xiong, A. Tuzhilin and Q. Liu, 2014. Cost-aware collaborative filtering for travel tour recommendations. ACM. Trans. Inf. Syst. TOIS., Vol. 32, 10.1145/2559169

Kazama, J.I., T. Makino, Y. Ohta and J.I. Tsujii, 2002. Tuning support vector machines for biomedical named entity recognition. Proceedings of the ACL-02 Workshop on Natural Language Processing in the Biomedical Domain, July 11-12, 2002, ACM, Stroudsburg, Pennsylvania, USA, pp: 1-8.

Konkol, M., T. Brychcin and M. Konopik, 2015. Latent semantics in named entity recognition. Expert Syst. Appl., 42: 3470-3479.
Direct Link  |  

Lafferty, J.D., A. McCallum and F.C.N. Pereira, 2001. Conditional random fields: Probabilistic models for segmenting and labeling sequence data. Proceedings of the 18th International Conference on Machine Learning, June 28-July 1, 2001, Williamstown, MA., USA., pp: 282-289.

Lample, G., M. Ballesteros, S. Subramanian, K. Kawakami and C. Dyer, 2016. Neural architectures for named entity recognition. Procceedings of the International Conference on NAACL, April 7-7, 2016, Cornell University Library Press, New York, USA., -.

Leaman, R., C.H. Wei and Z. Lu, 2015. TmChem: A high performance approach for chemical named entity recognition and normalization. J. Cheminf., 7: S1-S3.
CrossRef  |  Direct Link  |  

Lee, K.J., Y.S. Hwang and H.C. Rim, 2003. Two-phase biomedical NE recognition based on SVMs. Proceedings of the ACL 2003 Workshop on Natural Language Processing in Biomedicine, June 29-July 3, 2003, ACM, Stroudsburg, Pennsylvania, USA, pp: 33-40.

Li, K., W. Ai, Z. Tang, F. Zhang and L. Jiang et al., 2015. Hadoop recognition of biomedical named entity using conditional random fields. IEEE. Trans. Parallel Distrib. Syst., 26: 3040-3051.
CrossRef  |  Direct Link  |  

Liao, W. and S. Veeramachaneni, 2009. A simple semi-supervised algorithm for named entity recognition. Proceedings of the NAACL HLT 2009 Workshop on Semi-Supervised Learning for Natural Language Processing, June 4-4, 2009, ACM, Stroudsburg, Pennsylvania, USA, ISBN: 978-1-932432-38-1, pp: 58-65.

McNamee, P. and J. Mayfield, 2002. Entity extraction without language-specific resources. Proceedings of the 6th Conference on Natural Language Learning, August 31-September 1, 2002, ACM, Stroudsburg, Pennsylvania, USA, pp: 1-4.

Minkov, E., R.C. Wang and W.W. Cohen, 2005. Extracting personal names from email: Applying named entity recognition to informal text. Proceedings of the Conference on Human Language Technology and Empirical Methods in Natural Language Processing, October 6-8, 2005, ACM, Stroudsburg, Pennsylvania, USA., pp: 443-450.

Munro, R. and C.D. Manning, 2012. Accurate unsupervised joint named-entity extraction from unaligned parallel text. Proceedings of the 4th Workshop on Named Entity, July 12-12, 2012, ACM, Stroudsburg, Pennsylvania, USA, pp: 21-29.

Rau, L.F., 1991. Extracting company names from text. Proceedings of the 7th IEEE Conference on Artificial Intelligence Applications, February 24-28, 1991, Miami Beach, FL., pp: 29-32.

Saha, S.K., S. Sarkar and P. Mitra, 2009. Feature selection techniques for maximum entropy based biomedical named entity recognition. J. Biomed. Inf., 42: 905-911.
Direct Link  |  

Soderland, S., 1999. Learning information extraction rules for semi-structured and free text. J. Mach. Learn., 34: 233-272.
CrossRef  |  Direct Link  |  

Srihari, R., C. Niu and W. Li, 2000. A hybrid approach for named entity and sub-type tagging. Proceedings of the Sixth Conference on Applied Natural Language Processing, April 29-May 4, 2000, ACM, Stroudsburg, Pennsylvania, USA, pp: 247-254.

Tang, B., H. Cao, X. Wang, Q. Chen and H. Xu, 2014. Evaluating word representation features in biomedical named entity recognition tasks. BioMed. Res. Int., Vol. 2014,

Thielen, C., 1995. An approach to proper name tagging for German. Procceedings of the Conference on European Chapter of the Association for Computational Linguistics, June 28-29, 1995, SIGDAT Publisher, University of Tubingen Publisher, Tubingen, Germany, pp: 1-7.

World Travel & Tourism Council, 2015. Economic Impact of Travel and Tourism. World Travel & Tourism Council, London, England. https://www.wttc.org/research/economic-research/economic-impact-analysis/

Yang, M., L. Zhou, Z. Yu, S. Gao and J. Guo, 2015. Lao named entity recognition based on conditional random fields with simple heuristic information. Proceedings of the 2015 12th International Conference on Fuzzy Systems and Knowledge Discovery (FSKD), August 15-17, 2015, IEEE, Kunming, China, ISBN: 978-1-4673-7682-2, pp: 1426-1431.