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A Study of Current State of Work done for Classification in Indian Languages

Authors(2) :-Kaushika Pal, Dr. Biraj V. Patel

Classification has become an important aspect of study for storing, organizing and retrieving relevant document. So much work has been done in English language. Researchers have now started focusing on Indian language document classification as lot of content is available on web in Indian languages. The purpose of this paper is to study current work done in various Indian languages, and analyze the current situation and future scope to research in classification and related work on Indian languages.
Kaushika Pal, Dr. Biraj V. Patel
Classification, Machine Learning, Pre-processing, Data Mining, Natural Language Processing
  1. Harikrishnna D M, K. Sreenivasa Rao (2016). Emotion-Specific Features for Classifying Emotions in Story Text. IEEE 2016 22nd National Conference on Communication (NCC).
  2. Harikrishnna D M, K. Sreenivasa Rao (2015). Classification of Children Stories in Hindi Using Keywords and POS Density. In Proceedings of IEEE International Conference on Computer, Communication and Control.
  3. Harikrishnna D M, K. Sreenivasa Rao (2015). Children Story Classification based on Structure of the Story. IEEE International Conference on Advances in Computing, Communications and Informatics. (pp. 1485-1490).
  4. Harikrishnna D M, K. Sreenivasa Rao (2015). Multi-stage Children Story Speech Synthesis for Hindi. IEEE 2015 8th International Conference on Contemporary Computing (IC3).
  5. Megha Garg, Bhaskar Sinha (2015). Identification of Relations from IndoWordNet for Indian Languages using Support Vector Machine. IEEE International Conference on Computing and Network Communications. (pp. 547-552).
  6. Garima Nanda, Mohit Dua(2016). A Hindi Question Answering System using Machine Learning Approach. IEEE International Conference on Computational Techniques in Information and Communication Technologies.
  7. Vandana Jha, Manjunath N (2015). HOMS: Hindi Opinion Mining System. 2015 IEEE 2nd International Conference on Recent Trends in Information Systems. (pp. 366-371).
  8. Sumitra Pundlik, Prachi Kasbekar(2016). Multiclass Classification and Class based Sentiment Analysis for Hindi Language. IEEE International Conference on Advances in Computing, Communications and Informatics (sept 21-24, 2016) (pp. 512-518).
  9. Nidhi,Vishal Gupta(2012). Domain Based Classification of Punjabi Text Documents using Ontology and Hybrid Based Approach. Proceedings of the 3rd Workshop on South and Southeast Asian Natural Language Processing. (pp. 109-122).
  10. Nidhi,Vishal Gupta(2012). Algorithm for Punjabi Text Classification. International Journal of Computer Applications. Volume 37 - No. 11. (pp 30-35)
  11. Pratibha Singh, Ajay Verma, Narendra S. Chaudhari. Performance Analysis of Flexible zone based features to classify Hindi numerals. 2011 3rd International Conference on Electronics Computer Technology. (pp. 292 ? 296).
  12. Akanksha Gaur, Sunita Yadav. Handwritten Hindi Character Recognition using K- Means Clustering and SVM. 4th International Symposium on Emerging Trends and Technology in Libraries and Information Services.
  13. Richa Sharma, Shweta Nigam (2014). Opinion Mining In Hindi Language: A Survey. International Journal in Foundation of Computer Science & Technology. Vol. 4. No. 2. (pp. 41-47)
  14. Pooja Pandey, Sharvari Govilkar (2015). A Framework for Sentiment Analysis in Hindi using HSWN. International Journal of Computer Applications. Volume 119 No. 19. (pp. 23 - 26).
  15. Upendra Mishra, Chandra Prakash (2012). MAULIK: An Effective Stemmer for Hindi Language. International Journal on Computer Science and Engineering. Vol. 4 No. 5. (pp. 711-717).
  16. Dr. Hanumanthappa, Narayana Swamy.M (2015). Indian Language Text Mining. Journal of Software Engineering and Simulation. Vol. 2 Issue 10. (pp. 01-04).
  17. Piyush Arora (2013). Sentiment analysis for Hindi Language. (MS by Research Thesis). International Institute of Information Technology, Hyderabad.
  18. Uprendra Singh, Saqib Hasan(2015). Survey Paper on Document Classification ????????? and Classifiers. In International Journal of Computer Science and Technology - ?? Volum 3 Issue 2.(pp 83-87).
  19. Jasleen Kaur, Jatinderkumar Saini (2015). A study of Text Classification Natural Language Processing Algorithms for Indian Languages. VNSGU journal of ???????? Science and Technology. Volume 4. No.1 (pp. 162 - 167)’
  20. Yakshi Sharma,Veenu Mangat(2015). A Practical Approach to Sentiment ??????? Analysis of Hindi Tweets. International Conference on Next Generation ?? Computing Technologies.
  21. Senthil Kumar B, Bhabitha Varma E (2016). A survey on Text Categorization. International Journal of Advance ?? Research in Computer and ????? Communication Engineering. Vol. 5, Issue8. (pp. 286-289)
  22. Pooja Bolaj, Sharvan Govilkar(2016). A Survey on Text Categorization Techniques for Indian Regional Languages. International Journal of Computer ? Science and Information Technologies. Vol. 7(2). (pp. 480-483)
  23. Pooja Pandey and Sharvari Govilkar(2015). A survey of Sentiment Classification Techniques used for Indian Regional Languages. International Journal on Computational Science & Applications. Vol. 5, No. 2 (pp. 13-26)
  24. Hanumanthappa, Narayan Swamy M (2016). Indian Languages Text documents Categorization and Keyword Extraction. International Journal of computer Technology and Applications. Vol.9(3) (pp. 37-45)
Publication Details
  Published in : Volume 3 | Issue 7 | September-October 2017
  Date of Publication : 2017-10-31
License:  This work is licensed under a Creative Commons Attribution 4.0 International License.
Page(s) : 403-407
Manuscript Number : IJSRST173765
Publisher : Technoscience Academy
PRINT ISSN : 2395-6011
ONLINE ISSN : 2395-602X
Cite This Article :
Kaushika Pal, Dr. Biraj V. Patel, "A Study of Current State of Work done for Classification in Indian Languages", International Journal of Scientific Research in Science and Technology(IJSRST), Print ISSN : 2395-6011, Online ISSN : 2395-602X, Volume 3, Issue 7, pp.403-407, September-October-2017
URL : http://ijsrst.com/IJSRST173765