Abstract
This paper proposes a new approach for mining novel patterns from textual databases which considers both the mining process itself, the evaluation of this knowledge, and the human assessment. This is achieved by integrating Information Extraction technology and Genetic Algorithms to produce high-level explanatory novel hypotheses. Experimental results using the model are discussed and the assessment by human experts are highlighted.
This research is sponsored by the National Council for Scientific and Technological Research (FONDECYT, Chile) under grant number 1040469 “Un Modelo Evolucionario de Descubrimiento de Conocimiento Explicativo desde Textos con Base Semántica con Implicaciones para el Aná lisis de Inteligencia.”
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
Basu, S., Mooney, R., Pasupuleti, K., Ghosh, J.: Using Lexical Knowledge to Evaluate the Novelty of Rules Mined from Text. In: Proceedings of NAACL 2001 Workshop on WordNet and Other Lexical Resources: Applications, Extensions and Customizations, Pittsburg (June 2001)
Deb, K.: Multi-objective Optimization Using Evolutionary Algorithms. Wiley, Chichester (2001)
Foltz, P., Kintsch, W., Landauer, T.: The Measurement of Textual Coherence with Latent Semantic Analysis. Discourse processes 25(2), 259–284 (1998)
Han, J., Kamber, M.: Data Mining: Concepts and Techniques. Morgan Kaufmann, San Francisco (2001)
Hearst, M.: Text Mining Tools: Instruments for Scientific Discovery. In: IMA Text Mining Workshop, USA (April 2000)
Jurafsky, D., Martin, J.: Speech and Language Processing: An Introduction to Natural Language Processing, Computational Linguistics and Speech Recognition. Prentice Hall, Englewood Cliffs (2000)
Kintsch, W.: Predication. Cognitive Science 25(2), 173–202 (2001)
Swanson, D.: On the Fragmentation of Knowledge, the Connection Explosion, and Assembling Other People’s ideas. Annual Meeting of the American Society for Information Science and Technology 27(3) (February 2001)
Zitzler, E., Thiele, L.: An Evolutionary Algorithm for Multiobjective Optimisation: The Strength Pareto Approach. Technical Report 43, Swiss Federal Institute of Technology (ETH), Switzerland (1998)
Author information
Authors and Affiliations
Editor information
Editors and Affiliations
Rights and permissions
Copyright information
© 2005 Springer-Verlag Berlin Heidelberg
About this paper
Cite this paper
Atkinson-Abutridy, J.A. (2005). A Domain-Independent Approach to Discourse-Level Knowledge Discovery from Texts. In: Ali, M., Esposito, F. (eds) Innovations in Applied Artificial Intelligence. IEA/AIE 2005. Lecture Notes in Computer Science(), vol 3533. Springer, Berlin, Heidelberg. https://doi.org/10.1007/11504894_65
Download citation
DOI: https://doi.org/10.1007/11504894_65
Publisher Name: Springer, Berlin, Heidelberg
Print ISBN: 978-3-540-26551-1
Online ISBN: 978-3-540-31893-4
eBook Packages: Computer ScienceComputer Science (R0)