Resource Creation for Sentiment Analysis of Under-Resourced Language: Marathi-Reference-Cited by-同舟云学术

Resource Creation for Sentiment Analysis of Under-Resourced Language: Marathi

Published:2021 Issue: Volume: Page:445-457
ISSN:1865-0929
Container-title:Communications in Computer and Information Science
language:
Short-container-title:

Author:

Patil Rupali S.,Kolhe Satish R.

Publisher

Springer Singapore

Link

http://link.springer.com/content/pdf/10.1007/978-981-16-0507-9_37

Reference20 articles.

1. Kashyap, L., Joshi, S.R., Bhattacharyya, P.: Insights on Hindi WordNet coming from the IndoWordNet. In: Dash, N.S., Bhattacharyya, P., Pawar, J.D. (eds.) The WordNet in Indian Languages, pp. 19–44. Springer, Singapore (2017). https://doi.org/10.1007/978-981-10-1909-8_2

2. Google Translate. https://translate.google.com

3. Al-Sallab, A., Baly, R., Hajj, H., Shaban, K.B., El-Hajj, W., Badaro, G.: AROMA: a recursive deep learning model for opinion mining in Arabic as a low resource language. ACM Trans. Asian Low-Resource Lang. Inf. Process. (TALLIP) 16(4), 25:1–25:20 (2017)

4. Lecture Notes in Computer Science (Lecture Notes in Artificial Intelligence);KM Alomari,2017

5. Saif M., Salameh, M., Kiritchenko, S.: Sentiment lexicons for Arabic social media. In: Proceedings of the 10th Edition of the Language Resources and Evaluation Conference (LREC), pp. 33–37. Portoroz, Slovenia LREC (2016)

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3. Inflectional and Derivational Hybrid Stemmer for Sentiment Analysis: A Case Study with Marathi Tweets;Communications in Computer and Information Science;2022