Abstract
The Evaluation of a summary’s linguistic quality is a difficult task because several linguistic aspects (e.g. grammaticality, coherence, etc.) must be verified to ensure the well formedness of a text’s summary. In this paper, we report the result of combining “Adapted ROUGE” scores and linguistic quality features to assess linguistic quality. We build and evaluate models for predicting the manual linguistic quality score using linear regression. We construct models for evaluating the quality of each text summary (summary level evaluation) and of each summarizing system (system level evaluation). We assess the performance of a summarizing system using the quality of a set of summaries generated by the system. All models are evaluated using the Pearson correlation and the Root mean squared error.
Access this chapter
Tax calculation will be finalised at checkout
Purchases are for personal use only
References
Barzilay, R., Lapata, M.: Modeling local coherence: an entity-based approach. Comput. Linguist. 34(1), 1–34 (2008)
Conroy, J.M., Dang, H.T.: Mind the gap: dangers of divorcing evaluations of summary content from linguistic quality. In: Proceedings of the International Conference on Computational Linguistics, pp. 145–152 (2008)
Dell’Orletta, F., Wieling, M., Cimino, A., Venturi, G., Montemagni, S.: Assessing the readability of sentences: which corpora and features? In: Workshop on Innovative Use of NLP for Building Educational Applications, pp. 163–173 (2014)
Ellouze, S., Jaoua, M., Belguith, L.H.: An evaluation summary method based on a combination of content and linguistic metrics. In: Proceedings of RANLP Conference, pp. 245–251 (2013)
Falkenjack, J., Mühlenbock, K.H., Jönsson, A.: Features indicating readability in Swedish text. In: Proceedings of NoDaLiDa Conference, pp. 27–40 (2013)
Feng, L., Jansche, M., Huenerfauth, M., Elhadad, N.: A comparison of features for automatic readability assessment. In: Proceedings of COLING, pp. 276–284 (2010)
Finkel, J.R., Grenager, T., Manning, C.: Incorporating non-local information into information extraction systems by gibbs sampling. In: Proceedings of the Association for Computational Linguistics Conference, pp. 363–370 (2005)
Flesch, R.F.: How to Test Readability. Harper & Brothers, New York (1951)
Giannakopoulos, G., Karkaletsis, V., Vouros, G., Stamatopoulos, P.: Summarization system evaluation revisited: N-gram graphs. ACM Trans. Speech Lang. Process. J. 5(3), 1–39 (2008)
Graesser, A.C., Mcnamara, D.S., Louwerse, M.M., Cai, Z.: Coh-Metrix: Analysis of text on cohesion and language. Behav. Res. Methods Instrum. Comput. J. 36(2), 193–202 (2004)
Gunning, R.: The techniques of clear writing. McGraw-Hill, New York (1952)
Halliday, M.A.K., Hasan, R.: Cohesion in English. Longman, London (1976)
Islam, Z., Mehler, A.: Automatic readability classification of crowd-sourced data based on linguistic and information-theoretic features. Computacin Sistemas J. 17(2), 113–123 (2013)
Kate, R.J., Luo, X., Patwardhan, S., Franz, M., Florian, R., Mooney, R.J., Roukos, S., Welty, C.: Learning to predict readability using diverse linguistic features. In: Proceedings of Coling Conference, pp. 546–554 (2010)
Kincaid, J.P., Fishburne, Jr., R.P., Rogers, R.L., Chissom, B.S.: Derivation of new readability formulas for Navy enlisted personnel. Research Branch Report 8–75, U.S. Naval Air Station, Memphis (1975)
Louis, A., Nenkova, A.: Automatically assessing machine summary contentwithout a gold standard. Comput. Linguist. J. 39(2), 267–300 (2013)
Lin, C.Y.: Rouge: a package for automatic evaluation of summaries, text summarization branches out. In: Proceedings of the ACL-04 Workshop, pp. 74–81 (2004)
Lin, Z., Liu, C., Ng, H.T., Kan, M.Y.: Combining coherence models and machine translation evaluation metrics for summarization evaluation. In: Proceedings of Association for Computational Linguistics, pp. 1006–1014 (2012)
Pitler, E., Louis, A., Nenkova, A.: Automatic evaluation of linguistic quality in multi-document summarization. In: Proceedings of ACL, pp. 544–554 (2010)
Pitler, E., Nenkova, A.: Revisiting readability: a unified framework for predicting text quality. In: Proceedings of the EMNLP Conference, pp. 186–195 (2008)
Smith, E., Senter, R.: Automated readability index. AMRL-TR. Aerospace Medical Research Laboratories (6570th), 1 (1967)
Stolcke, A.: SRILM - an extensible language modeling toolkit. In: Proceedings of International Conference on Spoken Language Processing, vol. 2, pp. 901–904 (2002)
Author information
Authors and Affiliations
Corresponding author
Editor information
Editors and Affiliations
Rights and permissions
Copyright information
© 2016 Springer International Publishing Switzerland
About this paper
Cite this paper
Ellouze, S., Jaoua, M., Belguith, L.H. (2016). Automatic Evaluation of a Summary’s Linguistic Quality. In: Métais, E., Meziane, F., Saraee, M., Sugumaran, V., Vadera, S. (eds) Natural Language Processing and Information Systems. NLDB 2016. Lecture Notes in Computer Science(), vol 9612. Springer, Cham. https://doi.org/10.1007/978-3-319-41754-7_39
Download citation
DOI: https://doi.org/10.1007/978-3-319-41754-7_39
Published:
Publisher Name: Springer, Cham
Print ISBN: 978-3-319-41753-0
Online ISBN: 978-3-319-41754-7
eBook Packages: Computer ScienceComputer Science (R0)