Named entity recognition for Hindi language: A survey

References

• Mittal N, Agarwal B., Chouhan G., Pareek P., Bania N., “Discourse based Sentiment Analysis for Hindi Reviews,” In PReMI’13. 720–725, 2013.
   Google Scholar
• Greenwood, M. and Gaizauskas, R., “Using a Named Entity Tagger to Generalise Surface Matching Text Patterns for Question Answering,” In Workshop on Natural Language Processing for Question Answering 2007.
   Google Scholar
• Kumar, A. and Goyal, V., “Hindi to Punjabi machine translation based on statistical approach,” Journal of Statistics and Management Systems, 21(4), pp: 547-552, 2018. doi: 10.1080/09720510.2018.1466963
   Web of Science ®Google Scholar
• Kaur, Y. and Kaur, R. “Named Entity Recognition (NER) System for Hindi Language Using Combination of Rule Based Approach and List Look Up Approach”, In IJSRM, vol. 3(3), pp: 2300-2306, 2015.
   Google Scholar
• Morwal, S., Jahan, N. and Chopra, D., “Named Entity Recognition using Hidden Markov Model (HMM),” International Journal on Natural Language Computing, 1(4), pp: 15-23, 2013. doi: 10.5121/ijnlc.2012.1402
   Google Scholar
• Gayen, V. Sarkar, K., “A HMM Based Named Entity Recognition System for Indian Languages: The JU System at ICON 2013,” In arX-iv:1405.7397, 2014.
   Google Scholar
• Chopra, D., Joshi, N., Mathur, I., “Named Entity Recognition in Hindi Using Hidden Markov Model,” In 2nd International Conference on Computational Intelligence Communication Technology, 2016, pp: 581-586.
   Google Scholar
• Saha, S., Sarkar, S. and Mitra, P., “A Hybrid Feature Set Based Maximum Entropy Hindi Named Entity Recognition,” In IJCNLP, 2008, pp: 343-349.
   Google Scholar
• Ekbal, A., Bandyopadhyay, S., “Named Entity Recognition using Support Vector Machine: A Language Independent Approach,” In International Journal of Electrical, Computer and Systems Engineering, 590-604, 2010.
   Google Scholar
• Saha, S., Narayan, S., Sarkar, S. and Mitra, P., “A composite kernel for named entity recognition,” Pattern Recognition Letters, 31(12), pp: 1591-1597, 2010. doi: 10.1016/j.patrec.2010.05.004
   Web of Science ®Google Scholar
• Dandapat, S., Way, A., “Improved Named Entity Recognition using Machine Translation-based Cross-lingual Information,” In International Journal of Computing Science and Applications, vol. 20(3), 2016.
   Google Scholar
• Abhinaya, N., Neethu, J., Barathi, B., Kumar, A. Soman, K. P., “AMRITA_CEN@FIRE-2014: Named Entity Recognition for Indian Languages using Rich Features,” In the forum for the Information Retrieval Evaluation, 2014, pp: 103-111.
   Google Scholar
• Saharia, N., “Phone-based identification of language in code-mixed social network data,” Journal of Statistics and Management Systems, 20(4), pp: 565-574, 2017. doi: 10.1080/09720510.2017.1395176
   Web of Science ®Google Scholar
• Devi, G. R., Veena, P. V., Anand M. Soman, K. P., “Entity Extraction of Hindi-English and Tamil-English Code-Mixed Social Media Text,” In Forum for Information Retrieval Evaluation. Text Processing, 2018, pp: 206-218.
   Google Scholar
• Ekbal, A., Bandyopadhyay, S., “A Conditional Random Field Approach for Named Entity Recognition in Bengali and Hindi,” In Linguistic Issues in Language Technology-LiLT, vol. 2(1), pp: 1-44, 2009.
   Google Scholar
• Li, W. and McCallum, A., “Rapid Development of Hindi Named Entity Recognition using Conditional Random Field and Feature Induction (Short Paper),” In ACM Transaction on Asian Language Information Processing, 2(3), pp: 290-294, 2003. doi: 10.1145/979872.979879
   Google Scholar
• Saha, S., Mitra, P. and Sarkar, S., “A Semi-supervised Approach for maximum Entropy Based Hindi Named Entity Recognition,” In International Conf. on Pattern Recognition and Machine Intelligence, 2009, pp: 225-230. doi: 10.1007/978-3-642-11164-8_36
   Google Scholar
• Bhagavatula, M., GSK, S., Varma, V., “Named Entity Recognition an aid to improve multilingual entity filling in language-independent approach,” In Worksop on Information and Knowledge Management for Developing Region, 2012, pp: 3-10.
   Google Scholar
• Athavale, V., Bhardwaj, S., Pamecha, M., Prabhu, A. Shrivastava, S., “Towards Deep Learning in Hindi NER: An approach to tackle the Labelled Data Scarcity,” In NLPAI, 2016, pp: 154-160.
   Google Scholar
• Dhaka, V. S., Ramesh C. Poonia, and Linesh Raja. “The Realistic Mobility Evaluation of Vehicular Ad-Hoc Network for Indian Automotive Networks.” International Journal of Ad hoc, Sensor & Ubiquitous Computing 5.2, 2014, 1. doi: 10.5121/ijasuc.2014.5201
   Google Scholar
• Dhaka, V. S., R. C. Poonia, and L. Raja. “A literature review on dedicated short range communication for intelligent transport.” International Journal of Advanced Research in Computer Science and Software Engineering (IJARCSSE) 3.9, 2013, 1066-1071.
   Google Scholar
• Gupta, Shaurya, et al. “Tier Application in Multi-Cloud Databases to Improve Security and Service Availability.” Handbook of Research on Cloud Computing and Big Data Applications in IoT. IGI Global, 2019. 82-93. doi: 10.4018/978-1-5225-8407-0.ch005
   Google Scholar
• Srivastava, S., Sanglikar, M. and Kothari, D. C., “Named Entity Recognition System for Hindi Language: A Hybrid Approach,” In International Journal of Computational Linguistics, 2(1), pp: 10-22, 2011.
   Google Scholar
• Singh, V., et al. “Source Redundancy Management and Host Intrusion Detection in Wireless Sensor Networks.” Recent Patents on Computer Science 12.1, 2019.
   Google Scholar
• Chopra, D., Jahan, N., Morwal, S., “Hindi Named Entity Recognition by Aggregating Rule Based Heuristics and Hidden Markov Model,” In International Journal of Information Sciences and Techniques, 43-52, 2012. doi: 10.5121/ijist.2012.2604
   Google Scholar