Abstract
The theory of Human Plausible Reasoning (HPR) is an attempt by Collins and Michalski to explain how people answer questions when they are uncertain. The theory consists of a set of patterns and a set of inferences which could be applied on those patterns. This paper, investigates the application of HPR theory to the domain of cross language filtering. Our approach combines Natural Language Processing with HPR. The documents and topics are partially represented by automatically extracted concepts, logical terms and logical statements in a language neutral knowledge base. Reasoning provides the evidence of relevance. We have conducted hundreds of experiments especially with the depth of the reasoning, evidence combination and topic selection methods. The results show that HPR contributes to the overall performance by introducing new terms for topics. Also the number of inference paths from a document to a topic is an indication of its relevance.
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
Collins, A., Michalsky, R.: The Logic Of Plausible Reasoning A Core Theory. Cognitive Science 13, 1–49 (1989)
Collins, A., Burstein, M.: Modeling A Theory Of Human Plausible Reasoning. Artificial Intelligence III (2002)
Darrudi, E., Rahgozar, M., Oroumchian, F.: Human Plausible Reasoning for Question Answering Systems. In: International Conference on Advances in Intelligent Systems - Theory and Applications AISTA 2004 (2004)
Oroumchian, F., Arabi, B., Ashouri, E.: Using Plausible Inferences and Dempster-Shafer Theory of Evidence for Adaptive Information Filtering. In: 4th International Conference on Recent Advances in Soft Computing, pp. 248–254 (2002)
Karimzadehgan, K., Habibi, J., Oroumchian, F.: Logic-Based XML Information Retrival for Determining the Best Element to Retrive. In: Fuhr, N., Lalmas, M., Malik, S., Szlávik, Z. (eds.) INEX 2004. LNCS, vol. 3493, pp. 88–99. Springer, Heidelberg (2005)
Karimzadehgan, M., Belford, G., Oroumchian, F.: Expert Finding by Means of Plausible Inferences. In: International Conference on Information and Knowledge Engineering, IKE 2008, pp. 23–29 (2008)
Hugo, L.: MontyLingua: An end-to-end natural language processor with common sense (2004), http://web.media.mit.edu/~hugo/montylingua
Porter, M.F.: An algorithm for suffix stripping. Program 14(3), 130–137 (1980)
Author information
Authors and Affiliations
Editor information
Editors and Affiliations
Rights and permissions
Copyright information
© 2010 Springer-Verlag Berlin Heidelberg
About this paper
Cite this paper
Damankesh, A., Oroumchian, F., Shaalan, K. (2010). Multilingual Information Filtering by Human Plausible Reasoning. In: Peters, C., et al. Multilingual Information Access Evaluation I. Text Retrieval Experiments. CLEF 2009. Lecture Notes in Computer Science, vol 6241. Springer, Berlin, Heidelberg. https://doi.org/10.1007/978-3-642-15754-7_44
Download citation
DOI: https://doi.org/10.1007/978-3-642-15754-7_44
Publisher Name: Springer, Berlin, Heidelberg
Print ISBN: 978-3-642-15753-0
Online ISBN: 978-3-642-15754-7
eBook Packages: Computer ScienceComputer Science (R0)