|
[Sun15] Ming-Chieh Sung, Shi-Chung Chang, Peter B. Luh, 2015, Design of Personal Preference Inference from Questionnaire Data with Exemplary Application. Master Thesis, EE Dept., National Taiwan University, Taipei, Taiwan. [Hug68] Hughes, G., 1968. On the mean accuracy of statistical pattern recognizers. IEEE transactions on information theory, 14(1), pp.55-63. [YMS02] Yates, D., Moore, D.S. and Starnes, D.S., 2002. The practice of statistics: TI-83/89 graphing calculator enhanced. Macmillan. [BDV03] Bengio, Y., Ducharme, R., Vincent, P. and Jauvin, C., 2003. A neural probabilistic language model. Journal of machine learning research, 3(Feb), pp.1137-1155. [BFK95] Bies, A., Ferguson, M., Katz, K., MacIntyre, R., Tredinnick, V., Kim, G., Marcinkiewicz, M.A. and Schasberger, B., 1995. Bracketing guidelines for Treebank II style Penn Treebank project. University of Pennsylvania, 97, p.100. [Wal14] Waltz, D.L. ed., 2014. Semantic Structures (RLE Linguistics B: Grammar): Advances in Natural Language Processing (Vol. 23). Routledge. [EOR07] Erkan, G., Özgür, A. and Radev, D.R., 2007, June. Semi-supervised classification for extracting protein interaction sentences using dependency parsing. In EMNLP-CoNLL (Vol. 7, pp. 228-237). [JPK11] Han, J., Pei, J. and Kamber, M., 2011. Data mining: concepts and techniques. Elsevier. [MaJ00] Martin, J.H. and Jurafsky, D., 2000. Speech and language processing. International Edition, 710, p.25. [MYZ13] Mikolov, T., Yih, W.T. and Zweig, G., 2013, June. Linguistic regularities in continuous space word representations. In hlt-Naacl (Vol. 13, pp. 746-751). [SaT08] Sagae, K. and Tsujii, J.I., 2008, August. Shift-reduce dependency DAG parsing. In Proceedings of the 22nd International Conference on Computational Linguistics-Volume 1 (pp. 753-760). Association for Computational Linguistics. [SiA00] Siolas, G. and d''Alché-Buc, F., 2000. Support vector machines based on a semantic kernel for text categorization. In Neural Networks, 2000. IJCNN 2000, Proceedings of the IEEE-INNS-ENNS International Joint Conference on (Vol. 5, pp. 205-209). IEEE. [TCS13] Taiwan Communication Survey, phase one, year two, official questionnaire, 2013. [Online]. Available: http://www.crctaiwan.nctu.edu.tw/AnnualSurvey_detail_e.asp?ASD_ID=17 [WZH09] Wu, Y., Zhang, Q., Huang, X. and Wu, L., 2009, August. Phrase dependency parsing for opinion mining. In Proceedings of the 2009 Conference on Empirical Methods in Natural Language Processing: Volume 3-Volume 3 (pp. 1533-1541). Association for Computational Linguistics. [YLL05] Ye, Q., Lin, B. and Li, Y.J., 2005, August. Sentiment classification for Chinese reviews: A comparison between SVM and semantic approaches. In Machine Learning and Cybernetics, 2005. Proceedings of 2005 International Conference on (Vol. 4, pp. 2341-2346). IEEE. [Wor] Word2vec. Google. [Online]. Available: code.google.com/archive/p/word2vec/ [TuP10] Turney, P.D. and Pantel, P., 2010. From frequency to meaning: Vector space models of semantics. Journal of artificial intelligence research, 37, pp.141-188. [Fri96] Friedman, J., 1996. Another approach to polychotomous classification (Vol. 56). Technical report, Department of Statistics, Stanford University. [Dic] Dictionary.com. Definitions from Dictionary.com. [online] Available at: http://www.dictionary.com/ [Mer] Merriam-Webster Dictionary. Definition of clause by Merriam-Webster. [online] Available at: https://www.merriam-webster.com/dictionary/ [Sch05] Scherer, K.R., 2005. What are emotions? And how can they be measured?. Social science information, 44(4), pp.695-729. [MYM06] Martin, T.L., Yu, C.T., Martin, G.L. and Fazzio, D., 2006. On choice, preference, and preference for choice. The behavior analyst today, 7(2), p.234. [Sch15] Schultz, W., 2015. Neuronal reward and decision signals: from theories to data. Physiological Reviews, 95(3), pp.853-951. [Rey61] Reynolds, G.S., 1961. Relativity of response rate and reinforcement frequency in a multiple schedule. Journal of the Experimental Analysis of Behavior, 4(2), pp.179-184. [VaC15] Vapnik, V.N. and Chervonenkis, A.Y., 2015. On the uniform convergence of relative frequencies of events to their probabilities. In Measures of complexity(pp. 11-30). Springer International Publishing. [LaR10] Larson, R.K. and Ryokai, K., 2009. Grammar as science. Mit Press. [Hal84] Halliday, M.A., 1984. Language as code and language as behaviour: a systemic-functional interpretation of the nature and ontogenesis of dialogue. The semiotics of culture and language, 1, pp.3-35. [Mar92] Martin, J.R., 1992. English text: System and structure. John Benjamins Publishing. [EgS05] Eggins, S. and Slade, D., 2005. Analysing casual conversation. Equinox Publishing Ltd.. [HMM14] Halliday, M., Matthiessen, C.M. and Matthiessen, C., 2014. An introduction to functional grammar. Routledge. [YHL12] Yuan, G.X., Ho, C.H. and Lin, C.J., 2012. Recent advances of large-scale linear classification. Proceedings of the IEEE, 100(9), pp.2584-2603. [MLS13] Mikolov, T., Le, Q.V. and Sutskever, I., 2013. Exploiting similarities among languages for machine translation. arXiv preprint arXiv:1309.4168. [MSC13] Mikolov, T., Sutskever, I., Chen, K., Corrado, G.S. and Dean, J., 2013. Distributed representations of words and phrases and their compositionality. In Advances in neural information processing systems (pp. 3111-3119). [ChL11] Chang, C.C. and Lin, C.J., 2011. LIBSVM: a library for support vector machines. ACM transactions on intelligent systems and technology (TIST), 2(3), p.27. [MRT12] Mohri, M., Rostamizadeh, A. and Talwalkar, A., 2012. Foundations of machine learning. MIT press. [Pla99] Platt, J., 1999. Probabilistic outputs for support vector machines and comparisons to regularized likelihood methods. Advances in large margin classifiers, 10(3), pp.61-74. [RaD13] Rahman, M.M. and Davis, D.N., 2013. Addressing the class imbalance problem in medical datasets. International Journal of Machine Learning and Computing, 3(2), p.224. [MaM08] De Marneffe, M.C. and Manning, C.D., 2008. Stanford typed dependencies manual (pp. 338-345). Technical report, Stanford University. [TCS13] Taiwan Communication Survey, phase one, year two, official questionnaire, 2013. [Online]. Available: http://www.crctaiwan.nctu.edu.tw/AnnualSurvey_detail_e.asp?ASD_ID=17 [Rad04] Radford, A., 2004. English syntax: An introduction. Cambridge University Press. [McM92] McArthur, T.B. and McArthur, F., 1992. The Oxford companion to the English language. Oxford University Press, USA. [Kro05] Kroeger, P.R., 2005. Analyzing grammar: An introduction. Cambridge University Press. [Niv] Joakim Nivre, et el. Universal Dependencies. [Online]. Available: http://universaldependencies.org/u/dep/ [MMM06] De Marneffe, M.C., MacCartney, B. and Manning, C.D., 2006, May. Generating typed dependency parses from phrase structure parses. In Proceedings of LREC (Vol. 6, No. 2006, pp. 449-454). [Cry04] Crystal, D., 2004. The Cambridge encyclopedia of the English language. Ernst Klett Sprachen. [YaH10] Yao, H.C., Hsu, Y.S., 2010. On THSR’s Crisis Communication Strategies and the Effects. Journal of Communications Management. [LiS06] Lichtenstein, S. and Slovic, P. eds., 2006. The construction of preference. Cambridge University Press. [Bre56] Brehm, J.W., 1956. Postdecision changes in the desirability of alternatives. The Journal of Abnormal and Social Psychology, 52(3), p.384. [SMD09] Sharot, T., De Martino, B. and Dolan, R.J., 2009. How choice reveals and shapes expected hedonic outcome. Journal of Neuroscience, 29(12), pp.3760-3765. [GoL14] Goldberg, Y. and Levy, O., 2014. word2vec Explained: deriving Mikolov et al.''s negative-sampling word-embedding method. arXiv preprint arXiv:1402.3722. [MiC13] Mikolov, T., Chen, K., Corrado, G. and Dean, J., 2013. Efficient estimation of word representations in vector space. arXiv preprint arXiv:1301.3781. [Har54] Harris, Z.S., 1954. Distributional structure. Word, 10(2-3), pp.146-162. [Kow90] Kowalski, R.A., 1990. Problems and promises of computational logic. In Computational logic (pp. 1-36). Springer, Berlin, Heidelberg.
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