Discovering implicit intention-level knowledge from natural-language texts

Knowledge-Based Systems

Volumn 22, Issue 7, 2009, Pages 502-508

  Atkinson, John ^a   Ferreira, Anita ^a   Aravena, Elvis ^a  

^a UNIVERSITY OF CONCEPCIÓN   (Chile)

Author keywords

Natural language processing; Semantic analysis; Text mining

Indexed keywords

AUTOMATIC DISCOVERY; EVALUATION FUNCTION; EVOLUTIONARY COMPUTATIONS; EVOLUTIONARY METHOD; NATURAL-LANGUAGE PROCESSING; NEW APPROACHES; SEMANTIC ANALYSIS; TEXT MINING;

SEMANTICS;

LINGUISTICS;

EID: 69949100706     PISSN: 09507051     EISSN: None     Source Type: Journal    
DOI: 10.1016/j.knosys.2008.10.007     Document Type: Article

References (19)

1. R. Barzilay, M. Elhadad, Lexical chains for text summarization, in: Proceedings Meeting of the Association for Computational Linguistics of the ACL97/EACL97 Workshop on Intelligent Scalable Text Summarization, 1997, pp. 10-17.
2. R. Bekkerman, R. El-Yaniv, M. Tishby, On feature distributional clustering for text categorization, in: Proceedings of SIGIR-01, 24th ACM International Conference on Research and Development in Information Retrieval, 2001, pp. 146-153.
3. Bishop C. Pattern Recognition and Machine Learning (2006), Springer
4. Deb K. Multi-Objective Optimization using Evolutionary Algorithms (2001), John Wiley and Sons
5. DeJong K. Evolutionary Computation (2006), MIT Press
6. Duda R., Hart P., and Stork D. Pattern Classification. second ed. (2000), Wiley
7. Hastie T., Tibshirani R., and Friedman J. The Elements of Statistical Learning (2003), Springer
8. Jones G., Robertson A., and Santimetvirul C. Non-hierarchical document clustering using a genetic algorithm. Information Research 1 April (1995)
9. Jurafsky D., and Martin J. Speech and Language Processing: An Introduction to Natural Language Processing. Computational Linguistics and Speech Recognition (2000), Prentice Hall
10. J. Kupiec, J. Pedersen, F. Chen, A trainable document summarizer, in: Proceedings of the 18th ACM-SIGIR Conference, 1995, pp. 68-73.
11. Landauer T., McNamara D., Dennis S., and Kintsch W. Handbook of Latent Semantic Analysis (University of Colorado Institute of Cognitive Science Series) (2007), Lawrence Erlbaum Associates
12. Mann W., and Thompson S. Rhetorical structure theory: toward a functional theory of text organization. Text 8 3 (1998) 243-281
13. Manning C., and Schütze H. Foundations of Statistical Natural Language Processing (1999), The MIT Press
14. D. Marcu, The Rhetorical Parsing, Summarization, and Generation of Natural Language Texts, PhD Thesis, Department of Computer Science, University of Toronto, 1997.
15. Miller E., Shen D., Liu J., and Nicholas C. Performance and scalability of a large-scale n-gram based information retrieval system. Journal of Digital Information 1 5 (2000) 1-25
16. Neapolitan R. Learning Bayesian Networks (2003), Prentice Hall
17. Shawe J., and Cristianini N. Support Vector Machines and Other Kernel-based Learning Methods (2000), Cambridge University Press
18. Teufel S., and Moens M. Argumentative classification of extracted sentences as a first step towards flexible abstracting. In: Mani I., and Maybory M. (Eds). Advance in Automatic Text Summarization (1999), The MIT Press
19. Wang L. Support Vector Machines: Theory and Applications (2005), Springer