Abstract
Decision-making process has become extremely difficult especially for the large amount of textual data that companies must analyse to be competitive. The use of Natural Language Processing and Text mining in data discovery allows extracting knowledge from business texts that in the majority occur in unstructured form. The Decision Support System and the Information Technology departments face the new challenges that change poses, relying on linguistic analysis capabilities, no longer based on keyword research but on the syntactic properties, lexical and semantic word. In this paper, we focused on document-driven decision support, describing ways in which business communication performance can be improved by using a natural language interface as NooJ. In order to achieve our goals, we developed Linguistic Resources typically used in Economy knowledge domain, with regard to compound words and multi-word atomic linguistic units (MWALUs).
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References
Power, D.J.: Web-based and model-driven decision support systems: concepts and issues. In: AMCIS 2000 Proceedings, p. 387 (2000)
Power, D.J.: Decision support systems: a historical overview. In: Burstein, F., Holsapple, C.W. (eds.) Handbook on Decision Support Systems 1, pp. 121–140. Springer, Berlin Heidelberg (2008)
Sprague Jr., R.H., Carlson, E.D.: Building Effective Decision Support Systems. Prentice-Hall Inc, Englewood Cliffs (1982)
Škrobáčková, M., Kopáčková, H.: Decision support systems or business intelligence: what can help in decision-making? In: Provazniková, R., Kynclová, M. (eds.) Scientific papers of the University of Pardubice, Series D, Faculty of Economics and Administration, Pardubice, Czech Republic, vol. 10, pp. 98–103 (2006)
Fedorowicz, J.: Document based decision support in decision support for management. In: Sprague, Jr., R., Watson, H.J. (eds.) Decision Support for Management. Prentice-Hall, Upper Saddle River (1996)
Peterson, A.: Document-driven DSS resources. In: DSSResources.COM, December 2000. dssresources.com/dsstypes/docddss.html. Accessed 5 Feb 2016
Kopackova, H., Komarkova, J., Sedlak, P.: Decision making with textual and spatial information. WSEAS Trans. Inf. Sci. Appl. 5(3), 259 (2008)
Grimes, S.: A Brief History of Text Analytics. B Eye Network. http://www.b-eye-network.com/view/6311. Accessed 24 June 2016
Davenport, T.H., Harris, J.G.: Competing on Analytics: The New Science of Winning. Business School Press, Harvard (2007)
Gartner Research: Big Data (2013). http://www.gartner.com/it-glossary/big-data/. Accessed 20 March 2016
della Volpe, M.: Imprese tra Web 2.0 e Big Data. Nuove frontiere per innovazione e competitività, CEDAM (2013)
Radovanovic, M., Ivanovic, M.: Text mining approaches and applications. Novi Sad J. Math. 38(3), 227–234 (2008)
Feldman, R., Sanger, J.: The Text Mining Handbook. Cambridge University Press, Cambridge (2007)
Blomqvist, E.: The use of semantic web technologies for decision support – A survey. J. Seman. Web 5(3), 177–201 (2014). IOS Press, http://www.semantic-web-journal.net/sites/default/files/swj299_1.pdf
Kao, A., Poteet, R.S. (eds.): Natural Language Processing and Text Mining. Springer, London (2007)
De Bueriis, G., Elia, A. (eds.): Lessici elettronici e descrizioni lessicali, sintattiche, morfologiche ed ortografiche. Plectica, Salerno (2008)
Silberztein, M.: Nooj Manual (2003). http://www.nooj4nlp.net/NooJManual.pdf
Silberztein, M.: Corpus linguistics and semantic desambiguation. In: Maiello, G., Pellegrino, R. (eds.) Database, Corpora, Insegnamenti Linguistici, pp. 397–410. Schena Editore/Alain Baudry et C.ie, Fasano/Paris (2012)
Silberztein, M.: NooJ Computational Devices. In: Donabédian, A., Khurshudian, V., Silberztein, M. (eds.) Formalising Natural Languages with NooJ, pp. 1–13. Cambridge Scholars Publishing, Newcastle (2013)
Silberztein, M.: NooJ V4. In: Koeva, S., Mesfar, S., Silberztein, M. (eds.) Formalising Natural Languages with NooJ 2013, pp. 1–12. Cambridge Scholars Publishing, Newcastle (2013)
Silberztein, M.: Analyse et generation transformationnelle avec NooJ. In: Elia, A., Iacobini, C., Voghera, M. (eds.), Livelli di Analisi e Fenomeni di Interfaccia, Rome, Bulzoni (2015)
Silberztein, M.: La formalisation des langues: l’approche de NooJ. ISTE Ed, Londres (2015)
Elia, A., Martinelli, M., D’Agostino, E.: Lessico e strutture sintattiche: Introduzione alla sintassi del verbo italiano. Liguori Editore, Napoli (1981)
Elia, A., Monteleone, M., Esposito, F.: Dictionnaires électroniques et dictionnaires en ligne. Les Cahiers du dictionnaire 6, 43–62 (2014)
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Esposito, F., della Volpe, M. (2016). Using Text Mining and Natural Language Processing to Support Business Decision: Towards a NooJ Application. In: Barone, L., Monteleone, M., Silberztein, M. (eds) Automatic Processing of Natural-Language Electronic Texts with NooJ. NooJ 2016. Communications in Computer and Information Science, vol 667. Springer, Cham. https://doi.org/10.1007/978-3-319-55002-2_20
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DOI: https://doi.org/10.1007/978-3-319-55002-2_20
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