Создание цифровой библиотеки коллекции первопечатных славянских книг XV-XVI столетий

Main Article Content

Article Details

Библиографические ссылки

Chetviorkin I., Braslavskiy P., Loukachevich N. Sentiment analysis track at ROMIP 2011 // Computational Linguistics and Intellectual Technologies: Proceedings of the International Conference «Dialog 2012». 2012. P. 1-14.

Chetviorkin I., Loukachevitch N. Evaluating sentiment analysis systems in Russian // Proceedings of BSNLP workshop, ACL, Prague. 2013. P. 12-17.

Loukachevitch N., Blinov P., Kotelnikov E., Rubtsova Ju., Ivanov V., Tutubalina H. Sentirueval: testing object-oriented sentiment analysis systems in Russian // Computational Linguistics and Intellectual Technologies: Papers from the Annual International Conference «Dialogue». 2015. Issue 14. V. 2. P. 13-24.

Pang B., Lee L., Vaithyanathan S. Thumbs up? Sentiment classification using machine learning techniques // Proceedings of the ACL-02 Conference on Empirical Methods in Natural Language Processing. 2002. V. 10. P. 79-86.

Mullen T., Collier N. Sentiment analysis using support vector machines with diverse information sources // Proceedings of 9th EMNLP. 2004. P. 412-418.

Turney P. Thumbs up or thumbs down? Semantic orientation applied to unsupervised classification of reviews // Proceedings of the 40th ACL. 2002. P. 417-424.

Kudo T., Matsumoto Y. A boosting algorithm for classification of semi-structured text // Proceedings of 9th EMNLP. 2004. P. 301-308.

Matsumoto S., Takamura H., Okumura M. Sentiment classification using word sub-sequences and dependency sub-trees // Ho T.-B., Cheung D., Liu H. (eds.) PAKDD 2005. V. 3518. P. 301-311.

Mavljutov R.R., Ostapuk N.A. Using basic syntactic relations for sentiment analysis // Computational Linguistics and Intellectual Technologies: Proceedings of the International Conference «Dialog 2013». 2013. P. 91-100.

Yussupova N., Bogdanova D., Boyko M. Applying of sentiment analysis for texts in russian based on machine learning approach // Proceedings of The Second International Conference on Advances in Information Mining and Management, Italy. 2012. P. 8-14.

Furnkranz J., Mitchell T. M., Rilof E. A case study in using linguistic phrases for text categorization on the WWW // Proceedings of the AAAI Workshop on Learning for Text Categorization, Madison, US. 2998. P. 5-12.

Caropreso M.F., Matwin S., Sebastiani F.A. Learner-independent evaluation of the usefulness of statistical phrases for automated text categorization // Amita G. Chin (ed.), Text Databases and Document Management: Theory and Practice. 2006. P. 78-102.

Nastase V., Shirabad J.S., Caropreso M.F. Using dependency relations for text classification // Proceedings of the 19th Canadian Conference on Artificial Intelligence, Quebec City. 2006. P. 12-25.

Zhao S., Grishman R. Extracting relations with Integrated Information using kernel methods // Proceedings of the 43rd Annual Meeting of the ACL, Ann Arbor, US. 2005. P. 419-426.

Jansen B.J., Zhang M., Sobel K., Chowdury A. Twitter power: tweets as electronic word of mouth // Journal of the American Society for Information Science and Technology. 2009. V. 60, No 11. P. 2169-2188.

Go A., Bhayani R., Huang L. twitter sentiment classification using distant supervision // Technical report, Stanford. 2009.

Jiang L., Yu M., Zhou M., Liu X., Zhao T. Target-dependent Twitter sentiment classification // Proceedings of the 49th Annual Meeting of the Association for Computational Linguistics, Portland, US. 2011. P. 151-160.

Kouloumpis E., Wilson, T., Moore J. Twitter sentiment analysis: the good the bad and the omg! // Artificial Intelligence. 2011. P. 538-541.

Pak A., Paroubek P. Twitter as a corpus for sentiment analysis and opinion mining // Proceedings of LREC, Valetta. 2010. P. 75-100.

Адаскина Ю.В., Паничева П.В., Попов А.М. Полуавтоматическое пополнение словарей на основе синтаксических связей // Технологии информационного общества в науке, образовании и культуре: сборник научных статей. Труды XVII Всероссийской объединенной конференции «Интернет и современное общество» (IMS-2014), Санкт-Петербург, 19 – 20 ноября 2014 г. 2014. С. 271-276.

Зализняк А.А. Грамматический словарь русского языка. М.: Русский язык, 1980.

Pedregosa F., Varoquaux G., Gramfort A., Michel V., Thirion B., Grisel O., Blondel M., Prettenhofer P., Weiss R,, Dubourg V., Vanderplas J., Passos A., Cournapeau D., Brucher M., Perrot M., Duchesnay É. Scikit-learn: machine learning in Python // Journal of Machine Learning Research. 2011. V. 12 (Oct). P. 2825-2830.



Наиболее читаемые статьи этого автора (авторов)