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Dutch Journal of Applied Linguistics
Vol. 3:2 (2014) ► pp. 137154


Aha, D.W., Kibler, D., & Albert, M.K.
(1991) Instance-based learning algorithms. Machine Learning, 6, 37–66. CrossrefGoogle Scholar
Asur, S., & Huberman, B.A.
(2010) Predicting the future with social media. In Proceedings of the 2010 ieee/wic/acm International Conference on Web Intelligence and Intelligent Agent Technology, Vol 01 (pp. 492–499). Washington, DC, USA: IEEE Computer Society. CrossrefGoogle Scholar
Bagavandas, M., & Manimannan, G.
(2008) Style consistency and authorship attribution: A statistical investigation. Journal of Quantitative Linguistics, 15(1), 100–110. CrossrefGoogle Scholar
Barlow, M.
(2010) Individual usage: A corpus-based study of idiolects. In Laud conference , Landau, Germany. from http://​auckland​.academia​.edu​/MichaelBarlow
Carlberger, A., Carlberger, J., Magnuson, T., Hunnicutt, S., Cagigas, S.E.P., & Navarro, S.A.
(1997) Profet, a new generation of word prediction: An evaluation study. In ACL Workshop on Natural Language Processing for Communication Aids (pp. 23 -28).
Church, K.W.
(2000) Empirical estimates of adaptation: The chance of two noriegas is closer to p/2 than p2. In Proceedings of the 18th Conference on Computational Linguistics , Vol 1 (pp. 180–186).
Copestake, A.
(1997) Augmented and alternative nlp techniques for augmented and alternative nlp techniques for augmentative and alternative communication. In Proceedings of the ACL Workshop on Natural Language Processing for Communication Aids (pp. 37–42).
Daelemans, W., Van den Bosch, A., & Weijters, A.
(1997) Igtree: Using trees for compression and classiffication in lazy learning algorithms. Artificial Intelligence Review, 11, 407–423. CrossrefGoogle Scholar
Darragh, J.J., Witten, I.H., & James, M.L.
(1990) The reactive keyboard: A predictive typing aid. Computer, 23(11), 41–49. CrossrefGoogle Scholar
Eisner, J.
(1996) An empirical comparison of probability models for dependency grammar. In Technical Report IRCS-96-11, Institute for Research in Cognitive Science. University of Pennsylvania.
Fazly, A., & Hirst, G.
(2003) Testing the efficacy of part-of-speech information in word completion. In Proceedings of the 2003 eacl Workshop on Language Modeling for Text Entry Methods (pp. 9–16).
Garay-Vitoria, N., & Abascal, J.
(2006) Text prediction systems: A survey. Universal Access in the Information Society, 4(3), 188–203. CrossrefGoogle Scholar
Garay-Vitoria, N., & Gonzalez-Abascal, J.
(1997) Intelligent word-prediction to enhance text input rate. In Proceedings of the 2nd International Conference on Intelligent User Interfaces (pp. 241–244).
Haugen, E.
(1972) From idiolect to language. In E.S. Firchow, K. Grimstad, N. Hasselmo, & W.A. O’Neil (Eds.), Studies by Einar Haugen. Presented on the occasion of his 65th birthday (pp. 415–421). The Hague/Paris: Mouton.Google Scholar
Heil, B., & Piskorski, M.
(2009) New twitter research: Men follow men and nobody tweets( Blog No. June 1). http://​blogs​.hbr​.org​/cs​/2009​/06​/new\twitter\research\men\follo​.html.
Horstmann Koester, H., & Levine, S.P.
(1996) Effect of a word prediction feature on user performance. Augmentative and Alternative Communication, 12(3), 155–168. CrossrefGoogle Scholar
(1998) Model simulations of user performance with word prediction. Augmentative and Alternative Communication, 14(1), 25–35. CrossrefGoogle Scholar
How, Y., & Kan, M.-Y.
(2005, July). Optimizing predictive text entry for short message service on mobile phones. In M.J. Smith & G. Salvendy (Eds.), HCII ’05: Proceedings of the 11th International Conference on Human-Computer Interaction. Las Vegas, NV: Lawrence Erlbaum Associates.Google Scholar
Hunnicutt, S.
(1987) Input and output alternatives in word prediction. STL-QPSR, 28(2-3), 015–029.Google Scholar
Langlais, P., Foster, G., & Lapalme, G.
(2000) Transtype: A computer-aided translation typing system. In Proceedings of the 2000 NAACL-ANLP Workshop on Embedded Machine Translation Systems , Vol 5 (pp. 46–51).
Lesher, G.W., Moulton, B.J., & Higginbotham, D.J.
(1999) Effects of Ngram order and training text size on word prediction. In Proceedings of the Annual Conference of the Resna (pp. 52–55).
Louwerse, M.M.
(2004) Semantic variation in idiolect and sociolect: Corpus linguistic evidence from literary texts. Computers and the Humanities, 38(2), 207–221. CrossrefGoogle Scholar
Matiasek, J., Baroni, M., & Trost, H.
(2002) FASTY: A multi-lingual approach to text prediction. In Computers helping people with special needs (pp. 165–176). Berlin, Germany: Springer Verlag.Google Scholar
Mollin, S.
(2009) I entirely understand is a Blairism: The methodology of identifying idiolectal collocations. Journal of Corpus Linguistics, 14(3), 367–392. CrossrefGoogle Scholar
Nantais, T., Shein, F., & Johansson, M.
(2001) Efficacy of the word prediction algorithm in wordq. In Proceedings of the 24th Annual Conference on Technology and Disability , RESNA.
Oostdijk, N., Reynaert, M., Hoste, V., & Schuurman, I.
(2013) The construction of a 500-million-word reference corpus of contemporary written Dutch. In P. Spyns & J. Odijk (Eds.), Essential speech and language technology for Dutch (pp. 219–247). Berlin/Heidelberg: Springer. CrossrefGoogle Scholar
Rui, H., & Whinston, A.
(2012) Information or attention? An empirical study of user contribution on twitter. Information Systems and e-Business Management, 10(3), 309–324. CrossrefGoogle Scholar
Shein, F., Nantais, T., Nishiyama, R., Tam, C., & Marshall, P.
(2001) Word cueing for persons with writing difficulties: Wordq. In Proceedings of csun 16th Annual Conference on Technology for Persons with Disabilities .
Stocky, T., Faaborg, A., & Lieberman, H.
(2004) A commonsense approach to predictive text entry. In CHI ‘04: CHI ‘04 Extended abstracts on human factors in computing systems (pp. 1163–1166). New York, NY, USA: ACM.Google Scholar
Swiffin, A.L., Pickering, J.A., Arnott, J.L., & Newell, A.F.
(1985) PAL: An effort efficient portable communication aid and keyboard emulator. In Proceedings of the 8th Annual Conference on Rehabilitation Technology , resna (pp. 197–199).
Tanaka-Ishii, K.
(2007) Word-based predictive text entry using adaptive language models. Natural Language Engineering, 13(1), 51–74. CrossrefGoogle Scholar
Van den Bosch, A.
(2011) Effects of context and recency in scaled word completion. Computational Linguistics in the Netherlands Journal, 1, 79–94.Google Scholar
Van den Bosch, A., & Bogers, T.
(2008) Efficient context-sensitive word completion for mobile devices. In Mobilehci 2008: Proceedings of the 10th International Conference on Human-Computer Interaction with Mobile Devices and Services, IOP-MMI Special Track (pp. 465–470).
Verberne, S., Van den Bosch, A., Strik, H., & Boves, L.
(2012) The effect of domain and text type on text prediction quality. In Proceedings of the 13th Conference of the European Chapter of the Association for Computational Linguistics , Avignon, France (pp. 561–569). New Brunswick, NJ: ACL.
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