中文詞知識庫小組（2004）：《中文詞類分析》。台北市：中央研究院。
李琦瑋（2018年12月8日）。限塑收效：淨灘塑膠提袋量歷年最少：《國語日 報》，第一版。
宋曜廷、陳茹玲、李宜憲、查日龢、曾厚強、林維駿…張國恩（2013）：〈中 文文本可讀性探討：指標選取、模式建立與效度驗證〉。《中華心理學 刊》，55，75-106。
胡志偉、方文熙、李美綾（1994）：〈文章的適讀性指標〉。「第四屆世界華 語文教學研討會：語文分析組」，臺北，臺灣。
胡志偉、方文熙（1995）：〈中文讀者斷詞的一致性〉。「華人心理學家學術 研討會暨第三屆中國人的心理與行為科際研討會」，臺北，臺灣。
柯華葳、陳明蕾、廖家寧（2005）：〈詞頻、詞彙類型與眼球運動型態：來自 篇章閱讀的證據〉。《中華心理學刊》，47，381-398。
荊溪昱（1995）：〈中文國文教材的適讀性研究：適讀年級值的推估〉。《教 育研究資訊》，3，113-127。
馬建忠（1989）：《馬氏文通》。上海：商務印書館。
陳世敏（1972）：《中文可讀性公式試擬》（未出版之碩士論文）。政治大 學，臺北。
程祥徽、田小琳（2015）：《現代漢語》。台北市：書林出版有限公司。
黃居仁、謝舒凱、洪嘉馡、陳韻竹、蘇依莉、陳永祥、黃勝偉（2008）：〈中 文詞彙網路：跨語言知識處理基礎架構的設計理念與實踐〉。「第九屆漢 與詞彙語意學研討會（CLSW 2008）」，新加坡國立大學，新加坡。
黃昌寧、趙海（2007）：〈中文分詞十年回顧〉。《中文信息學報》，21，8-19。
曾昱翔、胡志偉、羅明、呂明蓁、呂菁菁（2014）：〈從文字屬性檢驗小學國 語課本生字之學習順序的恰當性〉。《教育心理學報》，46，251-270。
維基百科編輯者（2018年5月10日）。鄭成功。擷取自 https://zh.wikipedia.org/wiki/鄭成功。
Arnon, I. & Snider, N. (2010). More than words: Frequency effects for multi-word phrases. Journal of Memory and Language, 62, 67-82.
Baroni, M., Dinu, G., & Kruszewski, G. (2014, June). Dont count, predict! A systematic comparison of context-counting vs. context-predicting semantic vectors. Paper presented at the 52nd Annual Meeting of the Association for Computational Linguistics, Baltimore, MD.
Bahdanau, D., Cho, K., & Bengio, Y. (2015, May). Neural machine translation by jointly learning to align and translate. Paper presented at International Conference on Learning Representations 2015, San Deigo, CA.
Benjamin, R. G. (2012). Reconstructing Readability: Recent Developments and Recommendations in the Analysis of Text Difficulty. Educational Psychology Review, 24, 63-88.
Bengio, Y., Courville, A., & Vincent, P. (2013). Representation learning: A review and new perspectives. IEEE Transactions on Pattern Analysis and Machine Intelligence, 35, 1798-1828.
Blei, D. M., Edu, B. B., Ng, A. Y., Edu, A. S., Jordan, M. I., & Edu, J. B. (2003).
Latent dirichlet allocation. Journal of Machine Learning Research, 3, 993-1022.
Blei, D. M. (2012). Probabilistic topic models. Communications of the ACM, 55, 77-84.
Bormuth, J. R. (1966). Readability: A new approach. Reading Research Quarterly, 1,
79-132.
Bormuth, J. R. (1969). Development of readability analyses (Report No. 7-0052).
Chicago, IL: U.S. Department of Health, Education, and Welfare.
Bransford, J., & Franks, J. (1971). The abstraction of linguistic ideas. Cognitive Psychology, 2, 331–350.
Breiman, L. (2001). Statistical modeling: The two cultures. Statistical Science, 16, 199-231.
Caylor, J. S., Sticht, T. G., Fox, L. C., & Ford, J. P. (1973). Methodologies for Determining Reading Requirements Military Occupational Specialties (Report No. HumRRO-TR-73-5). Alexandria, VA: Human Resources Research
Organization.
Cawley, G. C., &Talbot, N. L. (2010). On over-fitting in model selection and subsequent selection bias in performance evaluation. Journal of Machine Learning Research, 11, 2079–2107.
Chall, J. S., & Dale, E. (1995). Readability revisited: the new Dale-Chall readability formula. Cambridge, MA: Brookline Books.
Chang, P., Galley, M., & Manning, C. (2008, June). Optimizing Chinese word
segmentation for machine translation performance. Paper presented at the Third Workshop on Statistical Machine Translation, Columbus, OH.
Chen, D., & Manning, C. (2014, October). A fast and accurate dependency parser using neural networks. Paper presented at 2014 Conference on Empirical Methods in Natural Language Processing, Doha, Qatar.
Cho, K., van Merrienboer, B., Gulcehre, C., Bahdanau, D., Bougares, F., Schwenk, H.
& Bengio, Y. (2014, October). Learning phrase representations using RNN Encoder-Decoder for statisitcal machine translation. Paper presented at the 2014
conference on Empirical Methods in Natural Language Procesing, Doha, Qatar.
Chomsky, N. (1956). Three models for the description of language. IRE Transactions on Information Theory, 2, 113-124.
Coleman, E. B. (1965). On understanding prose: Some determiners of its complexity (Report No. GB-2604). Washington, DC: National Science Foundation.
Connor, C. M., Morrison, F. J., Fishman, B. J., Schatschneider, C., & Underwood, P.
(2007). Algorithm-guided individualized reading instruction. Science, 315, 464-465.
Covington, M. A. (2001, March). A fundamental algorithm for dependency parsing.
Paper presented at 39th Annual ACM Southeast Conference, Athens, GA.
Crossley, S. A., Greenfield, J., & McNamara, D. S. (2008). Assessing text readability using cognitively based indices. TESOL Quarterly, 42, 475-493.
Dale, E. (1931). Evaluating Thorndike’s word list. Educational Research Bulletin, 10, 451-457.
Dale, E., & Chall, J. S. (1948). A formula for predicting readability. Educational Research Bulletin, 27, 37-54.
Dale, E., & Chall, J. S. (1949). The concept of readability. Elementary English, 26, 19-26.
Danielson, W. A., & Bryan, S. D. (1963). Computer automation of two readability formulas. Journalism Quarterly, 39, 201-206.
Davison, A., & Kantor, R. (1982). On the failure of readability formulas to define readable texts: A case study from adaptations. Reading Research Quarterly, 17, 187-209.
Devlin, J., Chang, M. W., Lee, K., & Toutanova, K. (2018). BERT: Pre-training of deep bidirectional transformers for language understanding. Retrieved from
https://arxiv.org/abs/1810.04805.
Diessel, H. (2007). Frequency effects in language acquisition, language use, and diachronic change. New Ideas in Psychology, 25, 104–123
Domingos, P. (2012). A few userful things to know about machine learning.
Communications of the ACM, 55, 78-87.
Dormann, C., Elith, J., Bacher, S., Bachmann, C., Carl, G., Carre, G., …Lautenbach, S. (2013). Collinearity: a review of methods to deal with it and a simulation study evaluating their performance. Ecography, 36, 27-46.
Dubay, W. H. (2004). The principles of readability. Costa Mesa, CA: Impact Information.
Dufty, D. F., Graesser, A. C., Louwerse, M. M., & McNamara, D. S. (2006).
Assigning grade levels to textbooks: Is it just readability? In R. Son (Ed.), Proceedings of the 28th annual meetings of the cognitive science society (pp.
1251-1256). Mahwah, NJ: Erlbaum.
Elman, J. L. (1990). Finding structure in time. Cognitive Science, 14, 179-211.
Farr, J. N., Jenkins, J. J., & Paterson., D. G. (1951). Simplification of the Flesch reading ease formula. Journal of Applied Psychology, 35, 333-357.
Fellbaum, C. (1998). WordNet: An electronic lexical database. Cambridge, MA: MIT Press.
Firth, J. R. (1957). A synopsis of linguistic theory 1930-1955. In Philological Society (Ed.), Studies in linguistic analysis (pp. 1-32). Oxford, England: Blackwell.
Flesch, R. (1943). Marks of a readable style: A study in adult education. New York:
NY: Columbia University.
Flesch, R. (1948). A new readability yardstick. Journal of Applied Psychology, 32, 221-233.
Foraker, S., & Murphy, G. L. (2012). Polysemy in sentence comprehension: Effects of meaning dominance. Journal of Memory Language, 67, 407-425.
Fry, E. (2002). Readability versus leveling. Reading Teacher, 56, 286-291.
Fry, E. B. (1977). Fry’s readability graph: Clarifications, validity, and extension to level 17. Journal of Reading, 21, 242-252.
Garnham, A. (1987). Mental models as representations of discourse and text. Upper Saddle River, NJ: Prentice Hall.
Gernsbacher, M. A., & Faust, M. E. (1991). The mechanism of suppression: A
component of general comprehension skill. Journal of Experimental Psychology.
Learning, Memory, and Cognition, 17, 245-262.
Gahl, S., & Yu, A. C. L. (Eds.). (2006). Special theme issue: Exemplar-based models in linguistics. The Linguistic Review, 23, 213–379.
Garnsey, S., Pearlmutter, N., Myers, E., & Lotocky, M. (1997). The contributions of verb bias and plausibility to the comprehension of temporarily ambiguous sentences. Journal of Memory and Language, 37, 58–93
Ghader, H., & Monz, C. (2017, November). What does attention in neural machine translation pay attention to? Paper presented at The 8th International Joint Conference on Natural Language Processing, Taipei, Taiwan.
Glenberg, A. M., & Epstein, W. (1987). Inexpert calibration of comprehension.
Memory & Cognition, 15, 84-93.
Graesser, A. C., & McNamara, D. S. (2011). Computational analyses of multilevel discourse comprehension. Topics in Cognitive Science, 3, 371-398.
Graesser, A. C., McNamara, D. S., & Kulikowich, J. M. (2011). Coh-Metrix:
Providing multilevel analyses of text characteristics. Educational Researcher, 40, 223-234.
Graesser, A. C., McNamara, D. S., Louwerse, M. M., & Cai, Z. (2004). Coh-Metrix:
Analysis of text on cohesion and language. Behavior Research Methods, Instruments, & Computers, 36, 193-202.
Graesser, A. C., Millis, K. K., & Zwaan, R. A. (1997). Discourse comprehension.
Annual Review of Psychology, 48, 163-189.
Graesser, A. C., Singer, M., & Trabasso, T. (1994). Constructing inferences during narrative text comprehension. Psychological Review, 101, 371-395.
Grice, P. (1975). Logic and Conversation. In P. Cole & J. L. Morgan (Eds.), Syntax and Semantics, Volume 3: Speech Acts (pp. 41-58). New York, NY: Academic Press.
Griffiths, T. L., Steyvers, M., & Tenenbaum, J. B. (2007). Topics in semantic representation. Psychological Review, 114, 211-244.
Gunning, R. (1952). The technique of clear writing. New York: McGraw-Hill.
Habel, C. U. (1982, July). Referential nets with attributes. Paper presented at the 9th Conference on Computational Linguistics, Prague, Czechoslovakia.
Hirschberg, J., & Manning, C. D. (2015). Advances in natural language processing.
Science, 349, 261-266.
Hoosain, R. (1992). Psychological reality of the word in Chinese. Language Processing in Chinese. Advances in Psychology, 90, 111-130.
Hochreiter, S., & Schmidhuber, J. (1997). Long short-term memory. Neural Computation, 9, 1735-1780.
Hsieh, S. K., Chiang, C. Y., Tseng, Y. H., Wang, B. Y., Chou T. L., & Lee, C. L.
(2017). Entrenchment and creativity in Chinese quadrasyllabic idiomatic
expressions. In Y. F. Wu, J. F. Hong, & Q. Su (Eds.), Chinese lexical semantics.
CLSW 2017. Cham, Switzerland: Springer.
Hsieh, S. K., Tseng, Y. H., Lee, C. Y., & Chiang, C. Y. (2018). Fluid Annotation: A granularity-aware annotation tool for Chinese word fluidity. Poster session presented at 11th Language Resources and Evaluation Conference, Miyazaki, Japan.
Huang, C. R., Hsieh, S. K., & Chen, K. J. (2017). Mandarin Chinese words and parts of speech. Oxford, England: Routledge.
Janssen, N., & Barber, H. (2012). Phrase frequency effects in language production.
PLoS ONE, 7. doi:10.1371/journal.pone.0033202
Johnson-Laird, P. N. (1980). Mental models in cognitive science. Cognitive Science, 4, 71-115.
Jurafsky, D., & Martin, H. M. (2008). Speech and language processing. Upper Saddle River, NJ: Prentice Hall.
Karpathy, A., Johnson, J., & Li, F. F. (2016, May). Visualizing and understanding recurrent networks. Paper presented at International converence on Learning Representations 2016, San Juan, Puerto Rico.
Kearns, K. (2011). Semantics. London, England: Palgrave.
Kintsch, W. (1988). The role of knowledge in discourse comprehension: A construction-integration model. Psychotocical Review, 95, 163-182.
Kintsch, W., & Dijk, T. A. (1978). Toward a model of text comprehension and production. Psychological Review, 85, 363-394.
Kintsch, W., & Mangalath, P. (2011). The construction of meaning. Topics in Cognitive Science, 3, 346-370.
Kintsch, W., & Vipond, D. (1979). Reading comprehension and readability in educational practice and psychological theory. In L. G.Nilsson (Ed.), Perspectives on memory research. Hillsdale, NJ: Erlbaum.
Kintsch, W., Welsch, D., Schmalhofer, F., & Zimny, S. (1990). Sentence memory: A theoretical analysis. Journal of Memory and Language, 29, 133-159.
Kizilcec, R. (2016, May). How much information? Effects of transparency on trust in an algorithmic interface. Paper presented at 2016 Conference on Human Factors in Computing System, San Jose, CA.
Klare, G. R. (1963). The measurement of readability. Ames, IA: Iowa State University Press.
Klare, G. R. (1974). Assessing readability. Reading Research Quarterly, 10, 62-102.
Klare, G. R. (1976). A second look at the validity of readability formulas. Journal of Literacy Research, 8, 129-152.
Klare, G. R. (1988). The formative years. In B. L. Zakaluk & S. J. Samuels (Eds.), Readability: Its past, present, and future (pp. 14-35). Newark, DE: International Reading Association.
Langacker, R. (1987). Foundations of cognitive grammar. Redwood City, CA:
Stanford University Press.
Landauer, T. K., & Dumais, S. T. (1997). A solution to Plato’s problem : The latent semantic analysis theory of acquisition, induction, and representation of knowledge. Psychological Review, 104, 211-240.
Liang, S., & Srikant, R. (2017). Why deep neural networks for function
approximation? Paper presented at 5th International Conference on Learning Representations, Toulon, France.
Lively, B. A., & Pressey, S. L. (1923). A method for measuring the “vocabulary burden” of textbooks. Educational Administration and Supervision, 9, 389-398.
Long, D. L., Golding, J. M., & Graesser, A. C. (1992). A test of the on-line status of goal-related inferences. Journal of Memory and Language, 31, 634-647.
Luong, M. T., Pham, H., Manning, C. D. (2015, September). Effective approaches to attention-based neural machine translation. Paper presented at EMNLP 2015:
Conference on Empirical Methods in Natual Language Processing, Lisbon, Portugal.
Lorge, I. (1939). Predicting reading difficulty of selections for children. Elementary English Review, 16, 229-233.
Ma, W. Y., & Chen, K. J. (2003, July). A bottom-up merging algorithm for Chinese unknown word extraction. Paper presented at the Second SIGHAN Workshop on Chinese Language Processing, Sapporo, Japan.
Manning, C. D. (2015). Computational linguistics and deep learning. Computational Linguistics, 41, 701-707.
Manning, C., Surdeanu, M., Bauer, J., Finkel, J., Bethard, S., & McClosky, D. (2014, June). The Stanford CoreNLP natural language processing toolkit. Paper
presented at 52nd Annual Meeting of the Association for Computational Linguistics, Baltimore, MD.
McCall, W. A., & Crabbs, L. M. (1961). Standard test lessons in reading. New York:
Bureau of Publications, Teachers College, Columbia University.
McCarthy, P. M., Dufty, D., Hempelmann, C., Cai, Z., Graesser, A. C., & McNamara, D. S. (2012). Newness and givenness of information: Automated identification in written discourse. In P. M. McCarthy & C. Boonthum (Eds.), Applied natural language processing and content analysis: Identification, investigation, and resolution (pp. 457-478). Hershey, PA: IGI Global.
McKoon, G., & Ratcliff, R. (1992). Inference during reading. Psychological Review, 99, 440-466.
McLaughlin, G. H. (1969). SMOG grading - a new readability formula. Journal of
Reading, 22, 639-646.
McNamara, D. S., Graesser, A. C., McCarthy, P. M., & Cai, Z. (2014). Automated evaluation of text and discourse with Coh-Metrix. New York, NY: Cambridge University Press.
McNamara, D. S., Kintsch, E., Songer, N. B., & Kintsch, W. (1996). Are good texts always better? Interactions of text coherence, background knowledge, and levels of understanding in learning from text. Cognition and Instruction, 14, 1-43.
McNamara, D., Ozuru, Y., & Floyd, R. (2011). Comprehension challenges in the fourth grade: The roles of text cohesion, text genre, and readers' prior
knowledge. International Electronic Journal of Elementary Education, 4, 229-257.
Meyer, B. J. F., Wijekumar, K., Middlemiss, W., Higley, K., Lei, P.-W., Meier, C., &
Spielvogel, J. (2010). Web-based tutoring of the structure strategy with or without elaborated feedback or choice for fifth- and seventh-grade readers.
Reading Research Quarterly, 45, 62-92.
Mikolov, T., Sutskever, I. Chen, K., Corrado, G., & Dean, J. (2013, December).
Distributed representations of words and phrases and their compositionality.
Paper presented at the 26th International Conference on Neural Information Processing Systems, Lake Tahoe, NV.
Miller, I. R., & Kintsch, W. (1980). Readability and recall of short pose passages: A theoretical analysis. Journal of Experimental Psychology: Human Learning and Memory, 6, 335-354.
Miller, L. R. (1974). Predictive powers of the Dale-Chall and Bormuth readability formulas. The Journal of Business Communication, 11, 21-30.
Mullis, I. V. S., & Martin, M. O. (2015). PIRLS 2016 assessment framework.
Chestnut Hill, MA: TIMSS & PIRLS International Study Center.
Nelson, J., Perfetti, C., Liben, D., & Liben, M. (2012). Measures of text difficulty:
Testing their predictive value for grade levels and student performance. New York, NY: Student Achievement Partners.
Ney, H. (1995). On the probabilistic interpretation of neural network classifiers and discriminative training criteria. IEEE Transactions on Pattern Analysis and Machine Intelligence, 17, 107-119.
Nivre, J., Marneffe, M., Ginter, F., Goldberg, Y., Hajic, J., Manning, C. D., …Zeman, D. (2016, May). Universal dependencies v1: A multilingual treebank collection.
Paper presented at the 10th International Conference on Language Resources and Evaluation, Portoroz, Slovenia.
Pearson, P. D. (2013). The effects of grammatical complexity on children’s
comprehension, recall, and conception of certain semantic relations. The Journal of Education, 193, 1-16.
Perfetti, C. (2007). Reading Ability: Lexical Quality to Comprehension. Scientific Studies of Reading, 11, 357-383.
Perfetti, C. A., Landi, N., & Oakhill, J. (2005). The acquisition of reading comprehension skill. In M. J. Snowling & C. Hulme (Eds.), The science of reading: A handbook (pp. 227-247). Malden, MA: Blackwell Publication.
Pinker, S., & Ullman, M. T. (2002). The past and future of the past tense. Trends in Cognitive Sciences, 6, 456–463.
Pylyshyn, Z. W. (1984). Computation and cognition: Toward a foundation for cognitive science. Cambridge, MA: The MIT Press.
Rapp, D. N., van den Broek, P., McMaster, K. L., Kendeou, P., & Espin, C. A.
(2007). Higher-order comprehension processes in struggling readers: A
perspective for research and intervention. Scientific Studies of Reading, 11, 289-312.
Rayner, K. (1998). Eye movements in reading and information processing: 20 years of research. Psychological Bulletin, 124, 372-422.
Rayner, K., & Duffy, S. A. (1986). Lexical complexity and fixation times in reading:
Effects of word frequency, verb complexity, and lexical ambiguity. Memory &
Cognition, 14, 191-201.
Rayner, K., Pollatsek, A., Ashby, J., & Clifton, C. (2012). Psychology of reading.
London, England: Psychology Press.
Rehurek, R., & Sojka, P. (2010, May). Software framework for topic modelling with large corpora. Paper presented at the seventh International Conference on Languae Resources and Evaluation, Valletta, Malta.
Ribeiro, M. T., Singh, S., & Guestrin, C. (2016, August). "Why should I trust you?":
Explaining the predictions of any classifier. Paper presented at the 22nd ACM SIGKDD International Conference on Knowledge Discovery and Data Mining, San Francisco, CA.
Rodd, J., Gaskell, G. & Marslen-Wilson, W. (2002). Making sense of semantic ambiguity: Semantic competition in lexical access. Journal of Memory and Language, 46, 245-266.
Rumelhart, D., & McClelland, J. (1986). On learning the past tenses of English verbs.
In D. Rumelhart & J. McClelland (Eds.), Parallel distributed processing:
Explorations in the microstructure of cognition (pp. 216-271). Cambridge, MA:
MIT Press.
Schriver, K. A. (2000). Readability formulas in the new millennium: What’s the use?
ACM Journal of Computer Documentation, 24, 105-106.
Schwarm, S. E., & Ostendorf, M. (2005, June). Reading level assessment using support vector machines and statistical language models. Paper presented at the 43rd Annual Meeting on Association for Computational Linguistics, Ann Arbor, MI.
Sherman, L. A. (1893). Analytics of literature: A manual for the objective study of English prose and poetry. Boston, MA: Ginn.
Shmueli, G. (2010). To explain or to predict. Statistical Science, 25, 289-310.
Smith, D. R., Stenner, A. J., Horabin, I., & Smith, M. (1989). The Lexile scale in theory and practice (Report No. NIH-HD-19448). Washington, D.C.:
MetaMetrics.
Song, H. A., Kim, B. K., Xuan, T. L., &Lee, S. Y. (2015). Hierarchical feature extraction by multi-layer non-negative matrix factorization network for classification task. Neurocomputing, 165, 63–74.
Stevens, K. C. (1980). Readability formulae and the McCall-Crabbs standard test lessons in reading. The Reading Teacher, 33, 413-415.
Stone, M. (1974). Cross-validation and multinomial prediction. Biometrika, 61, 509-515.
Sung, Y. T., Chang, T. H., Lin, W. C., Hsieh, K. S., & Chang, K. E. (2016). CRIE:
An automated analyzer for Chinese texts. Behavior Research Methods, 48, 1238-1251.
Sung, Y. T., Chen, J. L., Cha, J. H., Tseng, H. C., Chang, T. H., & Chang, K. E.
(2015). Constructing and validating readability models: The method of integrating multilevel linguistic features with machine learning. Behavior Research Methods, 47, 340-354.
Szalay, T. G. (1965). Validation of the Coleman readability formulas. Psychological
Reports, 17, 965-966.
Throndike, E. L. (1921). The teacher’s word book. New York: Columnbia University.
Toutanova, K., Klein, D., Manning, C. D., &Singer, Y. (2003, May). Feature-rich part-of-speech tagging with a cyclic dependency network. Paper presented at 2003 Human Language Technology Conference, Edmonton, Canada.
Trueswell, J. C., Tanenhaus, M. K., & Garnsey, S. M. (1994). Semantic influences on parsing: The use of thematic role information in syntactic ambiguity resolution.
Journal of Memory and Language, 33, 285–318.
Tseng, H. C., Hung, H. T., Sung, Y. T., & Chen, B. L. (2016, October). Classification of text readability based on deep neural network and representation learning techniques. Paper presented at the 2016 Conference on Computational Linguistics and Speech Processing, Tainan, Taiwan.
Tseng, H. S., Chang, P., Andrew, G., Jurafsky, D., & Manning, C. (2005, October). A conditional random field word segmenter. Paper presented at the Fourth
SIGHAN Workshop on Chinese Language Processing, Jeju Island, Korea.
Vasawani, A., Shazeer, N., Parmar, N., Uszkoreit, J., Jones, L.,
Gomez, …Polosukhin, I. (2017, December). Attention is all you need. Paper presented at 31st Conference on Neural Information Processing Systems, Long Beach, CA, USA.
van Dijk, T. A. (1976). Philosophy of action and theory of narrative. Poetics, 5, 287-338.
van Dijk, T. A., & Kintsch, W. (1983). Strategies of discourse comprehension. New York, NY: Academic Press.
Wagner, M. V., & Girasek, D. C. (2003). How readable are child safety seat installation instructions? Pediatrics, 111, 588-591.
Wallach, H. M., Mimno, D., &McCallum, A. (2009, December). Rethinking LDA:
Why priors matter. Paper presented at the 22nd International Conference on Neural Information Processing Systems, Vancouver, Canada.
Xue, N., & Shen, L. (2003, July). Chinese word segmentation as LMR tagging. Paper presented at the Second SIGHAN Workshop on Chinese Language Processing.
Sapporo, Japan.
Yamashita, T., Yamashita, K., &Kamimura, R. (2007). A stepwise AIC method for variable selection in linear regression. Communications in Statistics - Theory and Methods, 36, 2395–2403.
Yang, S. J. (1970). A readability formula for Chinese language. Madison, WI:
University of Wisconsin-Madison.
Zhu, M., Zhang, Y., Chen, W., Zhang, M., &Zhu, J. (2013, August). Fast and accurate shift-reduce constituent parsing. Paper presented at the 51st Annual Meeting of the Association for Computational Linguistics, Sofia, Bulgaria.
Zipf, G. K. (1949). Human behavior and the principle of least effort. Oxford, England: Addison-Wesley Press.
Zwaan, R. A., & Radvansky, G. (1998). Situation models in language comprehension and memory. Psychological Bulletin, 123, 162-185.