Abstract
In the man-machine interfaces, it is important to use dialogue understanding technologies. One of the practical application fields is a question and answering (QA) systems. In order to reply appropriate answers for user’s questions, this paper presents a dialogue technique by transforming semantic expressions for both requests and answers. The measurements for the disrepute of the QA system are introduced for requests and answers, respectively. For the KAMOKUMA QA system generating answers which are reflecting user’s intension, the presented scheme is applied. For the AQ data with 7,518 requests, the real time simulation to estimate user’s sufficiency is computed.
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
Aoe, J.: An efficient digital search algorithm by using a double-array structure. IEEE Trans. Softw. Engr. SE-15(9), 1066–1077 (1989)
Fuketa, M., et al.: A document classification method by using field association words. An Inter. J. of Inf. Sci. 126(1), 57–70 (2000)
Atlam, E.-S., et al.: Automatic Building of New Field Association Word Candidates Using Search Engine. Inf. Proc. & Manag (IPM) 42(4), 951–962 (2006)
Atlam, E.-S., et al.: Documents similarity measurement using field association terms. IPM 39, 809–824 (2003)
Kadoya, et al.: A Sentence Classification Technique by Using Intention Association Expressions. Computer Mathematics 82(7), 777–792 (2005)
Ferret, L., et al.: QALC: the Question-Answering system of LIMSI-CNRS. In: The Ninth Text Retrieval Conference (TREC-9), pp. 235–244 (2001)
Fukumoto, et al.: Question Answering Challenge (QAC1) Question answering evaluation at NTCIR Workshop 3. In: Third NTCIR Workshop Meeting: QAC1, pp. 1–10 (2002)
Pang, B., et al.: Thumbs up? Sentiment Classification using Machine Learning Techniques. In: EMNLP, pp. 79–86 (2002)
Kwon, O., Lee, J.: Text categorization based on k-nearest neighbor approach for Web site classification. In: IPM, vol. 39(1), pp. 25–44 (2003)
Lam, W., Ruiz, M., Srinivasan, P.: Automatic Text Categorization and Its Application to Text Retrieval. IEEE Trans. on KDE 11(6), 865–879 (1999)
Moens, M., Uyttendaele, C.: Automatic Text Structuring and Categorization as a First Step in Summarizing Legal Cases. IPM 33(6), 727–737 (1997)
Tokunaga, H., et al.: Estimating sentence types in computer related new product bulletins using a decision tree. Information Sciences 168(1-4), 185–200 (2004)
Fuketa, M., et al.: A Method of Extracting and Evaluating Good and Bad Reputations for Natural Language Expressions. Infor. Tech. & Deci. Making 4(2), 177–196 (2005)
Hatzivassiloglou, et al.: Effects of adjective orientation and readability on sentence subjectivity. In: COLING, pp. 299–305 (2000)
Yu, H., et al.: Towards Answering Opinion Questions: Separating Facts from Opinions and Identifying the Polarity of Sentences. In: EMNLP, pp. 129–136 (2003)
Hammond, et al.: FAQ Finder: A Case-Based Approach to Knowledge Navigation. In: CAIA, pp. 80–86 (1995)
Harada, J., et al.: Estimation of FAQ Knowledge Bases by Using Semantic Expressions for Questions and Answerd. International Journal of Computer Application in Technology 32(1), 69–81 (2008)
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
Inada, Y., Nakano, H., Kashiji, S., Aoe, J. (2009). Intelligent QA Systems Using Semantic Expressions. In: Velásquez, J.D., Ríos, S.A., Howlett, R.J., Jain, L.C. (eds) Knowledge-Based and Intelligent Information and Engineering Systems. KES 2009. Lecture Notes in Computer Science(), vol 5712. Springer, Berlin, Heidelberg. https://doi.org/10.1007/978-3-642-04592-9_39
Download citation
DOI: https://doi.org/10.1007/978-3-642-04592-9_39
Publisher Name: Springer, Berlin, Heidelberg
Print ISBN: 978-3-642-04591-2
Online ISBN: 978-3-642-04592-9
eBook Packages: Computer ScienceComputer Science (R0)