Abstract
This paper presents a flexible retrieval method for Q/A systems based on causal knowledge. Causality is not only a matter of causal statements, but also of conditional sentences. In conditional statements, causality generally emerges from the entailment relationship between the antecedent and the consequence. In this article, we present a method of retrieving conditional and causal sentences, in particular those identified by the presence of certain interrogative particles. These sentences are pre-processed to obtain both single cause-effect structures and causal chains. The knowledge base used to provide automatic answers based on causal relations are some medical texts, adapted to the described process. Causal paths permit qualifications in terms of weighting the intensity of the cause or the strength of links connecting causes to effects. A formalism that combines degrees of truth and McCulloch-Pitts cells enables us to weight the effect with a value and thereby obtain a flexible answer.
This is a preview of subscription content, log in via an institution.
Buying options
Tax calculation will be finalised at checkout
Purchases are for personal use only
Learn about institutional subscriptionsPreview
Unable to display preview. Download preview PDF.
References
Bunge, M.: Causality and modern sciences. Dover, New York (1979)
Puente, C., Olivas, J.A.: Analysis, detection and classification of certain conditional sentences in text documents. In: Proceedings of the 12th International Conference on Information Processing and Management of Uncertainty in Knowledge-Based Systems, IPMU 2008, Torremolinos, Spain (June 2008)
Girju, R.: Automatic detection of causal relations for question answering. In: Proc. of the 41st ACL Workshop on Multilingual Summarization and Question Answering (2003)
Paice, C., Black, W.: The use of causal expressions for abstracting and question-answering. In: Proc. of the 5th Int. Conf., on Recent Advances in Natural Language Processing, RANLP (2005)
Schmid, H.: Probabilistic Part-of-Speech Tagging Using Decision Trees. In: Proceedings of International Conference on New Methods in Language Processing (September 1994)
Paladini, D., Volpe, P.: Ultrasound of congenital fetal anomalies, differential diagnosis and prognostic indicators. Informa. healthcare (2007)
Pilu, G., Nicolaidesk, K.: Diagnosis of fetal abnormalities, the 12-23 weeks scan. Isoug & The Fetal Medicine Foundation (2002)
Nikolaidesk, K., Rizzo, G.: Doppler in obstetrics. The Fetal Medicine Foundation (2002)
Nikolaides, K.: The 11-13 weeks scan. The Fetal Medicine Foundation (2002)
Barbieri, R., Berga, S.: Precis: an update in Obstetrics & Gynecology. American College of Obstetricians and Gynecologists (2002)
Frank, R. (ed.): The explanatory power of models. Kluwer, Dordrecht (2002)
Helbig, H., Gnörlich, C.: Multilayered Extended Semantic Networks for Meaning Representation in NLP Systems. In: Gelbukh, A. (ed.) CICLing 2002. LNCS, vol. 2276, pp. 69–85. Springer, Heidelberg (2002)
Author information
Authors and Affiliations
Editor information
Editors and Affiliations
Rights and permissions
Copyright information
© 2009 Springer-Verlag Berlin Heidelberg
About this paper
Cite this paper
Puente, C., Sobrino, A., Olivas, J.Á. (2009). Extraction of Conditional and Causal Sentences from Queries to Provide a Flexible Answer. In: Andreasen, T., Yager, R.R., Bulskov, H., Christiansen, H., Larsen, H.L. (eds) Flexible Query Answering Systems. FQAS 2009. Lecture Notes in Computer Science(), vol 5822. Springer, Berlin, Heidelberg. https://doi.org/10.1007/978-3-642-04957-6_41
Download citation
DOI: https://doi.org/10.1007/978-3-642-04957-6_41
Publisher Name: Springer, Berlin, Heidelberg
Print ISBN: 978-3-642-04956-9
Online ISBN: 978-3-642-04957-6
eBook Packages: Computer ScienceComputer Science (R0)