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S. Štajner and Evans, R., Can Statistical Tests Be Used for Feature Selection in Diachronic Text Classification?, in Statistical Language and Speech Processing, vol. 7978, A. - H. Dediu, Martín-Vide, C., Mitkov, R., and Truthe, B. Berlin / Heidelberg: Springer, 2013, pp. 273-283.
D. - S. Chang and Choi, K. - S., Causal Relation Extraction Using Cue Phrase and Lexical Pair Probabilities, in Natural Language Processing – IJCNLP 2004, vol. 3248, K. - Y. Su, Tsujii, J. ’ichi, Lee, J. - H., and Kwong, O. Berlin / Heidelberg: Springer, 2005, pp. 61-70.
A. Kazantseva and Szpakowicz, S., Challenges in evaluating summaries of short stories, in Workshop on Task-Focused Summarization and Question Answering, Sydney, Australia, 2006, pp. 8–15.
D. Theijssen, Bosch, Lten, Boves, L., Cranen, B., and van Halteren, H., Choosing alternatives: Using Bayesian Networks and memory-based learning to study the dative alternation, Corpus Linguistics and Linguistic Theory, pp. 1–36, 2013.
R. Pishghadam and Sabouri, F., A Chronotopic Analysis of Cover Letters in Persian and English, Cross-Cultural Communication, vol. 7, 2011.
S. Crossley, A chronotopic approach to genre analysis: An exploratory study, English for Specific Purposes, vol. 26, pp. 4 - 24, 2007.
Y. Even-Zohar and Roth, D., A classification approach to word prediction, in 1st North American chapter of the Association for Computational Linguistics conference, Seattle, Washington, 2000.
A. Lampert, Dale, R., and Paris, C., Classifying speech acts using verbal response modes, in Australasian Language Technology Workshop (ALTW2006), Sydney, Australia, 2006.
L. Ahrenberg, Clause Restructuring in English-Swedish Translation, in Workshop on Annotation and Exploitation of Parallel Corpora AEPC 2010, Tartu, Estonia, 2010, pp. 34-43.
S. Stymne, Clustered Word Classes for Preordering in Statistical MachineTranslation, in 13th Conference of the European chapter of the Association for Computational Linguistics (EACL 2012), Avignon, France, 2012.
M. Santini, Clustering Web Pages to Identify Emerging Textual Patterns, in RÉCITAL 2005, Dourdan, 2005.
A. Kaster, Siersdorfer, S., and Weikum, G., Combining Text and Linguistic Document Representations for Authorship Attribution, 2005.
L. Rello and Ilisei, I., A Comparative Study of Spanish Zero Pronoun Distribution, in International Symposium on Data and Sense Mining, Machine Translation and Controlled Languages (ISMTCL), Besançon, France, 2009, pp. 209–214.
C. Samuelsson and Voutilainen, A., Comparing a Linguistic and a Stochastic Tagger, in 35th Annual Meeting of the Association for Computational Linguistics and Eighth Conference of the European Chapter of the Association for Computational Linguistics, Madrid, Spain, 1997.
M. Stevenson and Greenwood, M. A., Comparing Information Extraction Pattern Models, in Information Extraction Beyond The Document Workshop (COLING/ACL 2006), 2006.
A. Tutin, Comparing morphological and syntactic variations of support verb constructions and verbal full phrasemes in French: a corpus based study, in Relieving the pain in the neck in natural language processing. PARSEME 7th general meeting, Dubrovnik, Croatia, 2016.
R. Mitkov and Hallett, C., Comparing pronoun resolution algorithms, Computational Intelligence, vol. 23, no. 2, pp. 262–297, 2007.
N. Collier and Takeuchi, K., Comparison of character-level and part of speech features for name recognition in biomedical texts, Journal of Biomedical Informatics, vol. 37, pp. 423–435, 2004.
R. Evans, A Comparison of Rule-Based and Machine Learning Methods for Identifying Non-nominal It, in Natural Language Processing — NLP 2000, vol. 1835, D. N. Christodoulakis Berlin / Heidelberg: Springer, 2000, pp. 233-240.
K. Koskenniemi, Tapanainen, P., and Voutilainen, A., Compiling and Using Finite-State Syntactic Rules, in COLING-92, Nantes, France, 1992.
A. Arppe, Complex phenomena deserve complex explanations – choosing how to THINK in Finnish, in Quantitative Investigations in Theoretical Linguistics 2 (QITL-2), Osnabrück, Germany, 2006.
A. D. Evans, Lee, K., and Lyon, T. D., Complex Questions Asked by Defense Lawyers But Not Prosecutors Predicts Convictions in Child Abuse Trials, Law & Human Behavior, no. 33, pp. 258-264, 2008.
A. Neviarouskaya, Compositional Approach for Automatic Recognition of Fine-Grained Affect, Judgment, and Appreciation in Text, University of Tokyo, Tokyo, Japan, 2011.
A. Neviarouskaya, Prendinger, H., and Ishizuka, M., Compositionality Principle in Recognition of Fine-Grained Emotions from Text. 2009.
J. Foo, Computational Terminology : Exploring Bilingual and Monolingual Term Extraction, Linköping University, Linköping, 2012.

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