Abstract
We propose a query expansion method using Genetic Algorithms(GA) in Japanese. Recently, question answering research focuses on contextual questions. Therefore a question answering system has to resolve contextual problems by using both previous questions and previous answers. This problem is largely related to query expansion because of the need to find new keywords. In the contextual processing, a query needs to find other suitable keywords from related resources. Although it is easy for a system to find related words, it is difficult to find a suitable combination of keywords. GA is better suited for a combination problem just like a knapsack problem. Therefore we apply GA to our contextual query expansion method. In the evaluation experiment, MRR was 0.2531 in 360 contextual questions. We confirm the MRR of our method is higher than that of the baseline. We illustrate our method and the experiment.
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References
Voorhees, E.M.: Overview of the TREC 2004 Question Answering Track (2004)
Voorhees, E.M., Tice, D.M.: Building a question answering test collection. In: The 23 International ACM SIGIR Conference on Research and Development in Information Retrieval, vol. 78, pp. 200–207 (2000)
Kato, T., Fukumoto, J., Masui, F., Kando, N.: Handling Information. Access Dialogue through QA Technologies – A novel challenge. In: HLTNAACL 2004 Workshop on Pragmatics of Question Answering, pp. 70–77 (2004)
Murata, M., Utiyama, M., Isahara, H.: Japanese Question-Answering System Using Decreased Adding with Multiple Answers at NTCIR 5. In: NTCIR Workshop 5 Proceedings, pp. 380–385 (2005)
Goldberg, D.E.: Genetic Algorithms in Search, Optimization, and Machine Learning. Addison-Wesley, Reading (1989)
Mori, T., Kawaguchi, S.: Answering Contextual Questions Based on the Cohesion with the Knowledge. In: Proceedings of the Fifth NTCIR Workshop Meeting, pp. 386–393 (2005)
Chen, H., Shankaranarayanan, G., She, L., Iyer, A.: A Machine Learning Approach to Inductive Query by Examples: An Experiment Using Relevance Feedback, ID3, Genetic Algorithms, and Simulated Annealing. Journal of the American Society for Information Science 49(8), 693–705 (1998)
Xu, J., Croft, W.: Bruce Query Expansion Using Local and Global Document Analysis. In: Proceedings of the 19th Annual ACM-SIGIR Conference, pp. 4–11 (1996)
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Kimura, Y., Araki, K. (2006). Query Expansion for Contextual Question Using Genetic Algorithms. In: Ng, H.T., Leong, MK., Kan, MY., Ji, D. (eds) Information Retrieval Technology. AIRS 2006. Lecture Notes in Computer Science, vol 4182. Springer, Berlin, Heidelberg. https://doi.org/10.1007/11880592_48
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DOI: https://doi.org/10.1007/11880592_48
Publisher Name: Springer, Berlin, Heidelberg
Print ISBN: 978-3-540-45780-0
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