Abstract
Analysis is essential for solving complex problems such as diagnosing a patient, investigating an accident or predicting the outcome of a legal case. It is a non-trivial process even for human experts. To assist experts in this process we propose a CBR-based approach for automated problem analysis. In this approach a new problem is analysed by reusing reasoning knowledge from the analysis of a similar problem. To avoid the laborious process of manual case acquisition, the reasoning knowledge is extracted automatically from text and captured in a graph-based representation, which we dubbed Text Reasoning Graph (TRG), that consists of causal, entailment and paraphrase relations. The reuse procedure involves adaptation of a similar past analysis to a new problem by finding paths in TRG that connect the evidence in the new problem to conclusions of the past analysis. The objective is to generate the best explanation of how the new evidence connects to the conclusion. For evaluation, we built a system for analysing aircraft accidents based on the collection of aviation investigation reports. The evaluation results show that our reuse method increases the precision of the retrieved conclusions.
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References
Adeyanju, I.: Case reuse in textual case-based reasoning. Ph.D. thesis, Robert Gordon University (2011)
Aha, D.W., Breslow, L.A., Muñoz-Avila, H.: Conversational case-based reasoning. Applied Intelligence 14(1), 9–32 (2001)
Altenberg, B.: Causal linking in spoken and written English. Studia Linguistica 38(1), 20–69 (1984)
Androutsopoulos, I., Malakasiotis, P.: A survey of paraphrasing and textual entailment methods. Journal of Artificial Intelligence Research 38, 135–187 (2010)
Ashley, K., Lynch, C., Pinkwart, N., Aleven, V.: Toward modeling and teaching legal case-based adaptation with expert examples. In: McGinty, L., Wilson, D.C. (eds.) ICCBR 2009. LNCS, vol. 5650, pp. 45–59. Springer, Heidelberg (2009)
Bridge, D., Gomes, P., Seco, N.: Analysing air incident reports: workshop challenge. In: Proc. of the 4th Workshop on Textual Case-Based Reasoning (2007)
Bridge, D., Healy, P.: Ghostwriter-2.0: Product reviews with case-based support. In: Research and Development in Intelligent Systems XXVII, pp. 467–480. Springer (2011)
Brüninghaus, S., Ashley, K.D.: Progress in textual case-based reasoning: predicting the outcome of legal cases from text. In: Proceedings of the National Conference on Artificial Intelligence, vol. 21, p. 1577. AAAI Press, MIT Press, Menlo Park, Cambridge (2006)
Carthy, J., Wilson, D.C., Wang, R., Dunnion, J., Drummond, A.: Using T-ret system to improve incident report retrieval. In: Gelbukh, A. (ed.) CICLing 2004. LNCS, vol. 2945, pp. 468–471. Springer, Heidelberg (2004)
Cassidy, D., Carthy, J., Drummond, A., Dunnion, J., Sheppard, J.: The use of data mining in the design and implementation of an incident report retrieval system. In: 2003 IEEE Systems and Information Engineering Design Symposium, pp. 13–18. IEEE (2003)
Johnson, C.: Using case-based reasoning to support the indexing and retrieval of incident reports. In: Proceeding of European Safety and Reliability Conference (ESREL 2000): Foresight and Precaution, Balkema, Rotterdam, the Netherlands. pp. 1387–1394. Citeseer (2000)
Khoo, C.S.G.: Automatic identification of causal relations in text and their use for improving precision in information retrieval. Ph.D. thesis, The University of Arizona (1995)
Lamontagne, L., Lee, H.-H.: Textual reuse for email response. In: Funk, P., González Calero, P.A. (eds.) ECCBR 2004. LNCS (LNAI), vol. 3155, pp. 242–256. Springer, Heidelberg (2004)
Leacock, C., Miller, G.A., Chodorow, M.: Using corpus statistics and wordnet relations for sense identification. Computational Linguistics 24(1), 147–165 (1998)
Lenz, M., Burkhard, H.D.: Case retrieval nets: Basic ideas and extensions. In: Görz, G., Hölldobler, S. (eds.) KI 1996. LNCS, vol. 1137, pp. 227–239. Springer, Heidelberg (1996)
Miller, G.A.: Wordnet: a lexical database for English. Communications of the ACM 38(11), 39–41 (1995)
Orecchioni, A., Wiratunga, N., Massie, S., Chakraborti, S., Mukras, R.: Learning incident causes. In: Proc. of the 4th Workshop on Textual Case-Based Reasoning (2007)
Pearl, J.: Causality: models, reasoning and inference, vol. 29. Cambridge Univ. Press (2000)
Pechsiri, C., Piriyakul, R.: Explanation knowledge graph construction through causality extraction from texts. Journal of Computer Science and Technology 25(5), 1055–1070 (2010)
Recio-Garcıa, J.A., Dıaz-Agudo, B., González-Calero, P.A.: Textual cbr in jcolibri: From retrieval to reuse. In: Proceedings of the ICCBR 2007 Workshop on Textual Case-Based Reasoning: Beyond Retrieval, pp. 217–226. Citeseer (2007)
Swanson, R., Gordon, A.S.: Say anything: Using textual case-based reasoning to enable open-domain interactive storytelling. ACM Transactions on Interactive Intelligent Systems (TiiS) 2(3), 16 (2012)
Tsatsoulis, C., Amthauer, H.A.: Finding clusters of similar events within clinical incident reports: a novel methodology combining case based reasoning and information retrieval. Quality and Safety in Health Care 12(suppl. 2), ii24–ii32 (2003)
Wilke, W., Bergmann, R.: Techniques and knowledge used for adaptation during case-based problem solving. In: Mira, J., Moonis, A., de Pobil, A.P. (eds.) IEA/AIE 1998. LNCS, vol. 1416, pp. 497–506. Springer, Heidelberg (1998)
Wilson, D.C., Bradshaw, S.: Cbr textuality. In: Proceedings of the Fourth UK Case-Based Reasoning Workshop, pp. 67–80. Citeseer (1999)
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Sizov, G., Öztürk, P., Štyrák, J. (2014). Acquisition and Reuse of Reasoning Knowledge from Textual Cases for Automated Analysis. In: Lamontagne, L., Plaza, E. (eds) Case-Based Reasoning Research and Development. ICCBR 2014. Lecture Notes in Computer Science(), vol 8765. Springer, Cham. https://doi.org/10.1007/978-3-319-11209-1_33
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DOI: https://doi.org/10.1007/978-3-319-11209-1_33
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