Abstract
In this paper, we study the use of data mining techniques for stylistic analysis, from a linguistic point of view, by considering emerging sequential patterns. First, we show that mining sequential patterns of words with gap constraints gives new relevant linguistic patterns with respect to patterns built on n-grams. Then, we investigate how sequential patterns of itemsets can provide more generic linguistic patterns. We validate our approach from a linguistic point of view by conducting experiments on three corpora of various types of French texts (Poetry, Letters, and Fiction). By considering more particularly poetic texts, we show that characteristic linguistic patterns can be identified using data mining techniques. We also discuss how to improve our proposed approach so that it can be used more efficiently for linguistic analyses.
This is a preview of subscription content, log in via an institution.
Buying options
Tax calculation will be finalised at checkout
Purchases are for personal use only
Learn about institutional subscriptionsPreview
Unable to display preview. Download preview PDF.
References
Renouf, A., Sinclair, J.: Collocational Frameworks in English. In: English Corpus Linguistics: Studies in Honour of Jan Svartvik, pp. 128–143. Longman (1991)
Biber, D.: A corpus-driven approach to formulaic language in English. International Journal of Corpus Linguistics 14, 275–311 (2009)
Agrawal, R., Srikant, R.: Mining sequential patterns. In: Proc. of ICDE 1995, pp. 3–14 (1995)
Dong, G., Li, J.: Efficient minig of emerging patterns: Discovering trends and differences. In: Proc. of SIGKDD 1999, pp. 43–52 (1999)
Nanni, M., Rigotti, C.: Extracting trees of quantitative serial episodes. In: Proc. of KDID 2007, pp. 170–188 (2007)
Yan, X., Han, J., Afshar, R.: Clospan: Mining closed sequential patterns in large databases. In: Proc. of SDM 2003 (2003)
Dong, G., Pei, J.: Sequence Data Mining. Springer, Heidelberg (2007)
Ng, R., Lakshmanan, L., Han, J., Pang, A.: Exploratory mining and pruning optimizations of constrained associations rules. In: Proc. of SIGMOD 1998, pp. 13–24 (1998)
Plantevit, M., Crémilleux, B.: Condensed Representation of Sequential Patterns According to Frequency-Based Measures. In: Adams, N.M., Robardet, C., Siebes, A., Boulicaut, J.-F. (eds.) IDA 2009. LNCS, vol. 5772, pp. 155–166. Springer, Heidelberg (2009)
Author information
Authors and Affiliations
Editor information
Editors and Affiliations
Rights and permissions
Copyright information
© 2012 Springer-Verlag Berlin Heidelberg
About this paper
Cite this paper
Quiniou, S., Cellier, P., Charnois, T., Legallois, D. (2012). What about Sequential Data Mining Techniques to Identify Linguistic Patterns for Stylistics?. In: Gelbukh, A. (eds) Computational Linguistics and Intelligent Text Processing. CICLing 2012. Lecture Notes in Computer Science, vol 7181. Springer, Berlin, Heidelberg. https://doi.org/10.1007/978-3-642-28604-9_14
Download citation
DOI: https://doi.org/10.1007/978-3-642-28604-9_14
Publisher Name: Springer, Berlin, Heidelberg
Print ISBN: 978-3-642-28603-2
Online ISBN: 978-3-642-28604-9
eBook Packages: Computer ScienceComputer Science (R0)