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Comprehensive review reading list for Fall 2017 and Spring 2018 Artificial Intelligence/Knowledge Management
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tarix | 08.08.2018 | ölçüsü | 20,91 Kb. | | #61848 |
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COMPREHENSIVE REVIEW READING LIST for Fall 2017 and Spring 2018
Artificial Intelligence/Knowledge Management
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McCarthy, J., and Hayes, P.(1969) Some Philosophical Problems from the
Standpoint of Artificial Intelligence. Machine Intelligence. Vol. 4, p.463-502.
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Tversky, A. and D. Kahneman (1974). Judgment under Uncertainty: Heuristics and Biases. Science 185: 1124-1131.
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Stanfill, C. and Waltz, D. (1986) Toward Memory-Based Reasoning, Communications of the ACM, 29(12):1213-1228, December.
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Fahlman, S. and Hinton,G. (1987) Connectionist Architectures for Artificial Intelligence, IEEE Computer 20(1):100-109.
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L.B. Booker, D.E. Goldberg, J.H. Holland (1989). Classifier Systems and Genetic Algorithms. Artificial Intelligence, Volume 40, Issues 1–3, September 1989, Pages 235–282
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Alavi, M. and D. E. Leidner (2001). Knowledge Management and Knowledge Management Systems: Conceptual Foundations and Research Issues. MIS Quarterly 25(1): 107-136.
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Schultze, U. and D. E. Leidner (2002). Studying Knowledge Management in Information Systems Research: Discourses and Theoretical Assumptions. MIS Quarterly 26(3): 213-242.
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Woodridge, M., & Jennings, N. R. (1995). Intelligent Agents: Theory and Practice. The Knowledge Engineering Review,10(2), 115-152.
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Lawrence Page, Sergey Brin, Rajeev Motwani, Terry Winograd (1998). The PageRank citation ranking: Bringing order to the Web. 1998. Available at http://ilpubs.stanford.edu:8090/422/1/1999-66.pdf
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Wang, F-Y., Zeng, D., Carley, K. M., & Mao, W. (2007). Social Computing: From Social Informatics to Social intelligence. IEEE Intelligent Systems, 22(2), 79-83.
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Gueorgi Kossinets and Duncan J. Watts (2006), Empirical Analysis of an Evolving Social Network, Science, 311 (5757), 88-90.
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Adomavicius, G. and Tuzhillin, A. Toward the Next Generation of Recommender Systems: A Survey of the State-of-the-Art and Possible Extensions. IEEE Transactions on Knowledge and Data Engineering. 17(6), June 2005, 734-749.
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P Resnick, N Iacovou, M Suchak, P Bergstrom, J Riedl (1994). GroupLens: an open architecture for collaborative filtering of Netnews. Proceedings of the ACM 1994 Conference on Computer Supported Cooperative Work (CSCW’94).
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Sung-Pil Choi and Sung-HyonMyaeng (2012) Terminological Paraphrase Extraction from Scientific Literature Based on Predicate Argument Tuples. Journal of Information Science, 38(6) 593–611.
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S Deerwester, S T Landauer T K Dumais, G W Furnas, R A Harshman (1990). Indexing by Latent Semantic Analysis. Journal of the Society for Information Science. 41(6). Available at http://www.cob.unt.edu/itds/faculty/evangelopoulos/dsci5910/LSA_Deerwester1990.pdf.
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A L Berger, S A Della Pietra, V J Della Pietra (1996). A Maximum Entropy Approach to Natural Language Processing. Computational Linguistics, 1996.
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M. Simpson, and D. Demner-Fushman (2012) Biomedical Text Mining: A Survey of Recent Progress. C.C. Aggarwal and C.X. Zhai (eds.). Mining Text Data, Springer.
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LeCun, Yann, Yoshua Bengio, and Geoffrey Hinton (2015). Deep Learning, Nature 521( 7553), 436-444.
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C J C Burges (1998). A Tutorial on Support Vector Machines for Pattern Recognition. Data Mining and Knowledge Discovery. 2, p. 121-167. Available at http://research.microsoft.com/pubs/67119/svmtutorial.pdf
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Joachims, T. (1998). Text Categorization with Support Vector Machines: Learning with Many Relevant Features. Proceedings of the Tenth European Conference on Machine Learning. Available at http://www.cs.cornell.edu/people/tj/publications/joachims_98a.pdf
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Ghahramani, Z., & Jordan, M. I. (1997). Factorial Hidden Markov models, Machine Learning, 29, pp. 245–273
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Demetrios Zeinalipour-Yazti, Christos Laoudias, Constandinos Costa, Michail Vlachos, Maria I. Andreou, Dimitrios Gunopulos (2013). Crowd sourced Trace Similarity with Smartphones, IEEE Transactions on Knowledge & Data Engineering, vol.25, no. 6, pp. 1240-1253, June 2013
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Anind K. Dey, Daniel Salber and Gregory D. Abowd (2001). A Conceptual Framework and a Toolkit for Supporting the Rapid Prototyping of Context-aware Applications. Human Computer Interaction. 16 (2-4), pp. 97-166
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Philemon Brakel and Dirk Stroobandt and Benjamin Schrauwen, Training Energy-Based Models for Time-Series Imputation, Journal of Machine Learning Research, pp. 2771-2797, 2013
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Abbasi, Ahmed; Zhang, Zhu; Zimbra, David; Chen, Hsinchun; and Nunamaker, Jay F. Jr.. (2010). "Detecting Fake Websites: The Contribution of Statistical Learning Theory," MIS Quarterly, (34: 3) pp.435-461.
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Hevner, A.R., March, S.T., Jinsoo Park, J. and Ram, S. (2004).Design Science in Information Systems Research. MIS Quarterly. 28(1), 75-105.
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