Abstract
Classifier-independent measures are important to assess the quality of corpora. In this paper we present supervised and unsupervised measures in order to analyse several data collections for studying the following features: domain broadness, shortness, class imbalance, and stylometry. We found that the investigated assessment measures may allow to evaluate the quality of gold standards. Moreover, they could also be useful for classification systems in order to take strategical decisions when tackling some specific text collections.
This research work was partially supported by the CICYT TIN2006-15265-C06 project.
This is a preview of subscription content, log in via an institution to check access.
Access this chapter
Tax calculation will be finalised at checkout
Purchases are for personal use only
Preview
Unable to display preview. Download preview PDF.
References
Debole, F., Sebastiani, F.: An analysis of the relative hardness of Reuters-21578 subsets. Journal of the American Society for Information Science and Technology 56(6), 584–596 (2005)
Wibowo, W., Williams, H.: On using hierarchies for document classification. In: Proc. of the Australian Document Computing Symposium, pp. 31–37 (1999)
Herdan, G.: Type-Token Mathematics: A Textbook of Mathematical Linguistics. Mouton & Co., The Hague (1960)
Tweedie, F.J., Baayen, R.H.: How variable may a constant be?: Measures of lexical richness in perspective. Computers and the Humanities 32(5), 323–352 (1998)
Hoover, D.L.: Another perspective on vocabulary richness. Computers and the Humanities 37(2), 151–178 (2004)
Japkowicz, N.: The class imbalance problem: Significance and strategies. In: Proc. of the 2000 International Conference on Artificial Intelligence (IC-AI 2000), vol. 1, pp. 111–117 (2000)
Montejo-Ráez, A.: Automatic text categorization of documents in the High Energy Physics domain. Phd thesis, Granada University, Spain (2006)
Diederich, J., Kindermann, J., Leopold, E., Paass, G.: Authorship attribution with support vector machines. Applied Intelligence 19(1-2), 109–123 (2004)
Can, F., Patton, J.M.: Change of writing style with time. Computers and the Humanities 38(1), 61–82 (2004)
Hoover, D.L.: Corpus stylistics, stylometry, and the styles of henry james. Style 41(2), 174–203 (2007)
Brants, T., Popat, A.C., Xu, P., Och, F.J., Dean, J.: Large language models in machine translation. In: Proc. of the 2007 Joint Conference on Empirical Methods in Natural Language Processing and Computational Natural Language Learning (EMNLP-CoNLL), pp. 858–867 (2007)
Màrquez, L., Padró, L.: A flexible pos tagger using an automatically acquired language model. In: Proc. of the 35th annual meeting on Association for Computational Linguistics, pp. 238–245 (1997)
Ponte, J.M., Croft, W.B.: A language modeling approach to information retrieval. In: Research and Development in Information Retrieval, pp. 275–281 (1998)
Bahl, L.R., Jelinek, E., Mercer, R.L.: A maximum likelihood approach to continuous speech recognition. IEEE Transactions on Pattern Analysis and Machine Intelligence 5(2), 179–190 (1983)
Brown, P.F., Pietra, V.J.D., de Souza, P.V., Lai, J.C., Mercer, R.L.: Class-based n-gram models of natural language. Computational Linguistics 18(4), 467–479 (1992)
Zipf, G.K.: Human behaviour and the principle of least effort. Addison-Wesley, Reading (1949)
Cardoso-Cachopo, A., Oliveira, A.: Combining LSI with other classifiers to improve accuracy of single-label text categorization. In: First European Workshop on Latent Semantic Analysis in Technology Enhanced Learning - EWLSATEL 2007 (2007)
Pinto, D., Benedí, J.M., Rosso, P.: Clustering narrow-domain short texts by using the Kullback-Leibler distance. In: Gelbukh, A. (ed.) CICLing 2007. LNCS, vol. 4394, pp. 611–622. Springer, Heidelberg (2007)
Agirre, E., Soroa, A.: Semeval-2007 task 2: Evaluating word sense induction and discrimination systems. In: Proc. of the 4th International Workshop on Semantic Evaluations - SemEval 2007, pp. 7–12. Association for Computational Linguistics (2007)
Kendall, M.: A new measure of rank correlation. Biometrika 30, 81–89 (1938)
Author information
Authors and Affiliations
Editor information
Editors and Affiliations
Rights and permissions
Copyright information
© 2010 Springer-Verlag Berlin Heidelberg
About this paper
Cite this paper
Pinto, D., Rosso, P., Jiménez-Salazar, H. (2010). On the Assessment of Text Corpora. In: Horacek, H., Métais, E., Muñoz, R., Wolska, M. (eds) Natural Language Processing and Information Systems. NLDB 2009. Lecture Notes in Computer Science, vol 5723. Springer, Berlin, Heidelberg. https://doi.org/10.1007/978-3-642-12550-8_23
Download citation
DOI: https://doi.org/10.1007/978-3-642-12550-8_23
Publisher Name: Springer, Berlin, Heidelberg
Print ISBN: 978-3-642-12549-2
Online ISBN: 978-3-642-12550-8
eBook Packages: Computer ScienceComputer Science (R0)