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Enis Sert. 2013. Word Context and Token Representations from Paradigmatic Relations and Their Application to Part-of-Speech Induction. MS Thesis, September. Koç University. [fulbright, ai.ku] url pdf google scholar
Alexandre Allauzen , Hugo Larochelle , Christopher Manning and Richard Socher , editors. 2013. Proceedings of the Workshop on Continuous Vector Space Models and their Compositionality, Sofia, Bulgaria, August. Association for Computational Linguistics. [fulbright] url google scholar books
Tomas Mikolov, Wen-tau Yih and Geoffrey Zweig. 2013. Linguistic Regularities in Continuous Space Word Representations. In Proceedings of the 2013 Conference of the North American Chapter of the Association for Computational Linguistics: Human Language Technologies, pp 746--751, Atlanta, Georgia, June. Association for Computational Linguistics. [fulbright] url google scholar
Mehmet Ali Yatbaz, Enis Sert and Deniz Yuret. 2012. Learning Syntactic Categories Using Paradigmatic Representations of Word Context. In Proceedings of the 2012 Conference on Empirical Methods in Natural Language Processing (EMNLP-CONLL 2012), Jeju, Korea, July. Association for Computational Linguistics. [ai.ku, fulbright, scode, upos] url google scholar
Eric H Huang, Richard Socher, Christopher D Manning and Andrew Y Ng. 2012. Improving word representations via global context and multiple word prototypes. In Proceedings of the 50th Annual Meeting of the Association for Computational Linguistics: Long Papers-Volume 1, pp 873--882. Association for Computational Linguistics. [fulbright] google scholar
Ronan Collobert, Jason Weston, Léon Bottou, Michael Karlen, Koray Kavukcuoglu and Pavel Kuksa. 2011. Natural language processing (almost) from scratch. The Journal of Machine Learning Research, vol 12, pp 2493--2537. JMLR. org. [fulbright] google scholar
Mehmet Ali Yatbaz and Deniz Yuret. 2010. Unsupervised part of speech tagging using unambiguous substitutes from a statistical language model. In Proceedings of the 23rd International Conference on Computational Linguistics: Posters, pp 1391--1398, August. Association for Computational Linguistics. [ai.ku, fulbright] url google scholar
Deniz Yuret and Mehmet Ali Yatbaz. 2010. The Noisy Channel Model for Unsupervised Word Sense Disambiguation. Computational Linguistics, vol 36, no 1, pp 111--127, March. MIT Press. [ai.ku, fulbright] pdf google scholar
Joseph Reisinger and Raymond J Mooney. 2010. Multi-prototype vector-space models of word meaning. In Human Language Technologies: The 2010 Annual Conference of the North American Chapter of the Association for Computational Linguistics, pp 109--117. Association for Computational Linguistics. [fulbright] google scholar
Tomas Mikolov, Martin Karafiát, Lukas Burget, Jan Cernock\`y and Sanjeev Khudanpur. 2010. Recurrent neural network based language model.. In INTERSPEECH, pp 1045--1048. [fulbright] pdf google scholar
Peter D Turney, Patrick Pantel, et al. 2010. From frequency to meaning: Vector space models of semantics. Journal of artificial intelligence research, vol 37, no 1, pp 141--188. [fulbright] google scholar
Lili Kotlerman, Ido Dagan, Idan Szpektor and Maayan Zhitomirsky-Geffet. 2010. Directional distributional similarity for lexical inference. Natural Language Engineering, vol 16, no 4, pp 359--389. Cambridge Univ Press. [ddsim, fulbright] pdf pdf google scholar
Mehmet Ali Yatbaz and Deniz Yuret. 2009. Unsupervised morphological disambiguation using statistical language models. In NIPS 2009 Workshop on Grammar Induction, Representation of Language and Language Learning, Vancouver, Canada, December. [ai.ku, fulbright] url google scholar
Ronan Collobert and Jason Weston. 2008. A unified architecture for natural language processing: Deep neural networks with multitask learning. In Proceedings of the 25th international conference on Machine learning, pp 160--167. ACM. [fulbright] google scholar
D. Chandler. 2007. Semiotics: The Basics. Taylor & Francis. [fulbright] url google scholar books
Andriy Mnih and Geoffrey Hinton. 2007. Three new graphical models for statistical language modelling. In Proceedings of the 24th international conference on Machine learning, pp 641--648. ACM. [fulbright] google scholar
M. Sahlgren. 2006. The Word-Space Model: Using distributional analysis to represent syntagmatic and paradigmatic relations between words in high-dimensional vector spaces. Stockholm University. [upos, fulbright] pdf google scholar
David M. Blei, Andrew Y. Ng and Michael I. Jordan. 2003. Latent Dirichlet Allocation. Journal of Machine Learning Research. [Bayes, Dirichlet, npbayes, fulbright] url pdf google scholar
Hinrich Schütze. 1995. Distributional part-of-speech tagging. In Proceedings of the seventh conference on European chapter of the Association for Computational Linguistics, pp 141--148. Morgan Kaufmann Publishers Inc.. [fulbright] google scholar
Hinrich Schütze and Jan Pedersen. 1993. A vector model for syntagmatic and paradigmatic relatedness. In Proceedings of the 9th Annual Conference of the UW Centre for the New OED and Text Research, pp 104--113. Citeseer. [fulbright] google scholar
Susan T Dumais, George W Furnas, Thomas K Landauer, Scott Deerwester and Richard Harshman. 1988. Using latent semantic analysis to improve access to textual information. In Proceedings of the SIGCHI conference on Human factors in computing systems, pp 281--285. ACM. [fulbright] google scholar

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