{"status":"ok","message-type":"work","message-version":"1.0.0","message":{"indexed":{"date-parts":[[2024,9,5]],"date-time":"2024-09-05T12:54:54Z","timestamp":1725540894884},"publisher-location":"Berlin, Heidelberg","reference-count":17,"publisher":"Springer Berlin Heidelberg","isbn-type":[{"type":"print","value":"9783642105081"},{"type":"electronic","value":"9783642105098"}],"content-domain":{"domain":[],"crossmark-restriction":false},"short-container-title":[],"published-print":{"date-parts":[[2009]]},"DOI":"10.1007\/978-3-642-10509-8_34","type":"book-chapter","created":{"date-parts":[[2009,11,11]],"date-time":"2009-11-11T08:36:24Z","timestamp":1257928584000},"page":"308-316","source":"Crossref","is-referenced-by-count":1,"title":["Experimental Investigation of Three Machine Learning Algorithms for ITS Dataset"],"prefix":"10.1007","author":[{"given":"J. L.","family":"Yearwood","sequence":"first","affiliation":[],"role":[{"role":"author","vocabulary":"crossref"}]},{"given":"B. H.","family":"Kang","sequence":"additional","affiliation":[],"role":[{"role":"author","vocabulary":"crossref"}]},{"given":"A. V.","family":"Kelarev","sequence":"additional","affiliation":[],"role":[{"role":"author","vocabulary":"crossref"}]}],"member":"297","reference":[{"key":"34_CR1","doi-asserted-by":"publisher","first-page":"129","DOI":"10.1023\/A:1020911318981","volume":"3","author":"A.M. Bagirov","year":"2002","unstructured":"Bagirov, A.M., Rubinov, A.M., Yearwood, J.: A global optimization approach to classification. Optim. Eng.\u00a03, 129\u2013155 (2002)","journal-title":"Optim. Eng."},{"key":"34_CR2","volume-title":"Bioinformatics: The Machine Learning Approach","author":"P. Baldi","year":"2001","unstructured":"Baldi, P., Brunak, S.: Bioinformatics: The Machine Learning Approach. MIT Press, Cambridge (2001)"},{"key":"34_CR3","series-title":"Lecture Notes in Artificial Intelligence","doi-asserted-by":"crossref","first-page":"416","DOI":"10.1007\/11790853_33","volume-title":"Advances in Data Mining. Applications in Medicine, Web Mining, Marketing, Image and Signal Mining","author":"S. Huda","year":"2006","unstructured":"Huda, S., Ghosh, R., Yearwood, J.: A variable initialization approach to the EM algorithm for better estimation of the parameters of Hidden Markov Model based acoustic modeling of speech signals. In: Perner, P. (ed.) ICDM 2006. LNCS (LNAI), vol.\u00a04065, pp. 416\u2013430. Springer, Heidelberg (2006)"},{"key":"34_CR4","doi-asserted-by":"crossref","unstructured":"Huda, S., Yearwood, J., Ghosh, R.: A hybrid algorithm for estimation of the parameters of Hidden Markov Model based acoustic modeling of speech signals using constraint-based genetic algorithm and expectation maximization. In: Proceedings of ICIS 2007, the 6th Annual IEEE\/ACIS International Conference on Computer and Information Science, Melbourne, Australia, July 11-13, pp. 438\u2013443 (2007)","DOI":"10.1109\/ICIS.2007.23"},{"issue":"1","key":"34_CR5","doi-asserted-by":"publisher","first-page":"182","DOI":"10.1109\/TSMCB.2008.2004051","volume":"39","author":"S. Huda","year":"2009","unstructured":"Huda, S., Yearwood, J., Togneri, R.: A constraint based evolutionary learning approach to the expectation maximization for optiomal estimation of the Hidden Markov Model for speech signal modeling. IEEE Transactions on Systems, Man, Cybernetics, Part B\u00a039(1), 182\u2013197 (2009)","journal-title":"IEEE Transactions on Systems, Man, Cybernetics, Part B"},{"key":"34_CR6","series-title":"Lecture Notes in Artificial Intelligence","doi-asserted-by":"publisher","first-page":"187","DOI":"10.1007\/11961239_17","volume-title":"Advances in Knowledge Acquisition and Management","author":"B.H. Kang","year":"2006","unstructured":"Kang, B.H., Kelarev, A.V., Sale, A.H.J., Williams, R.N.: A new model for classifying DNA code inspired by neural networks and FSA. In: Hoffmann, A., Kang, B.-h., Richards, D., Tsumoto, S. (eds.) PKAW 2006. LNCS (LNAI), vol.\u00a04303, pp. 187\u2013198. Springer, Heidelberg (2006)"},{"key":"34_CR7","doi-asserted-by":"crossref","DOI":"10.1002\/9780470316801","volume-title":"Finding Groups in Data: An Introduction to Cluster Analysis","author":"L. Kaufman","year":"1990","unstructured":"Kaufman, L., Rousseeuw, P.J.: Finding Groups in Data: An Introduction to Cluster Analysis. John Wiley & Sons, New York (1990)"},{"key":"34_CR8","unstructured":"Kelarev, A.V., Kang, B.H., Sale, A.H.J., Williams, R.N.: Labeled directed graphs and FSA as classifiers of strings. In: 17th Australasian Workshop on Combinatorial Algorithms, AWOCA 2006, Uluru (Ayres Rock), Northern Territory, Australia, July 12\u201316, pp. 93\u2013109 (2006)"},{"key":"34_CR9","series-title":"Lecture Notes in Artificial Intelligence","doi-asserted-by":"publisher","first-page":"1027","DOI":"10.1007\/11941439_116","volume-title":"AI 2006: Advances in Artificial Intelligence","author":"A. Kelarev","year":"2006","unstructured":"Kelarev, A., Kang, B., Steane, D.: Clustering algorithms for ITS sequence data with alignment metrics. In: Sattar, A., Kang, B.-h. (eds.) AI 2006. LNCS (LNAI), vol.\u00a04304, pp. 1027\u20131031. Springer, Heidelberg (2006)"},{"key":"34_CR10","unstructured":"Lee, K., Kay, J., Kang, B.H.: KAN and RinSCut: lazy linear classifier and rank-in-score threshold in similarity-based text categorization. In: Proc. ICML 2002 Workshop on Text Learning, University of New South Wales, Sydney, Australia, pp. 36\u201343 (2002)"},{"key":"34_CR11","first-page":"186","volume":"2","author":"G.S. Park","year":"2005","unstructured":"Park, G.S., Park, S., Kim, Y., Kang, B.H.: Intelligent web document classification using incrementally changing training data set. J. Security Engineering\u00a02, 186\u2013191 (2005)","journal-title":"J. Security Engineering"},{"key":"34_CR12","doi-asserted-by":"crossref","unstructured":"Sattar, A., Kang, B.H.: Advances in Artificial Intelligence. In: Proceedings of AI 2006, Hobart, Tasmania (2006)","DOI":"10.1007\/11941439"},{"key":"34_CR13","doi-asserted-by":"publisher","first-page":"49","DOI":"10.1071\/SB00039","volume":"15","author":"D.A. Steane","year":"2002","unstructured":"Steane, D.A., Nicolle, D., Mckinnon, G.E., Vaillancourt, R.E., Potts, B.M.: High-level relationships among the eucalypts are resolved by ITS-sequence data. Australian Systematic Botany\u00a015, 49\u201362 (2002)","journal-title":"Australian Systematic Botany"},{"key":"34_CR14","unstructured":"WEKA, Waikato Environment for Knowledge Analysis, http:\/\/www.cs.waikato.ac.nz\/ml\/weka"},{"key":"34_CR15","doi-asserted-by":"crossref","unstructured":"Washio, T., Motoda, H.: State of the art of graph-based data mining, SIGKDD Explorations. In: Dzeroski, S., De Raedt, L. (eds.) Editorial: Multi-Relational Data Mining: The Current Frontiers; SIGKDD Exploration\u00a05(1), 59\u201368 (2003)","DOI":"10.1145\/959242.959249"},{"key":"34_CR16","volume-title":"Data Mining: Practical Machine Learning Tools and Techniques with Java Implementations","author":"I.H. Witten","year":"2005","unstructured":"Witten, I.H., Frank, E.: Data Mining: Practical Machine Learning Tools and Techniques with Java Implementations. Morgan Kaufmann, San Francisco (2005)"},{"key":"34_CR17","volume-title":"Classification Technologies: Optimization Approaches to Short Text Categorization","author":"J.L. Yearwood","year":"2007","unstructured":"Yearwood, J.L., Mammadov, M.: Classification Technologies: Optimization Approaches to Short Text Categorization. Idea Group Inc., USA (2007)"}],"container-title":["Lecture Notes in Computer Science","Future Generation Information Technology"],"original-title":[],"link":[{"URL":"http:\/\/link.springer.com\/content\/pdf\/10.1007\/978-3-642-10509-8_34.pdf","content-type":"unspecified","content-version":"vor","intended-application":"similarity-checking"}],"deposited":{"date-parts":[[2020,11,23]],"date-time":"2020-11-23T21:56:57Z","timestamp":1606168617000},"score":1,"resource":{"primary":{"URL":"http:\/\/link.springer.com\/10.1007\/978-3-642-10509-8_34"}},"subtitle":[],"short-title":[],"issued":{"date-parts":[[2009]]},"ISBN":["9783642105081","9783642105098"],"references-count":17,"URL":"https:\/\/doi.org\/10.1007\/978-3-642-10509-8_34","relation":{},"ISSN":["0302-9743","1611-3349"],"issn-type":[{"type":"print","value":"0302-9743"},{"type":"electronic","value":"1611-3349"}],"subject":[],"published":{"date-parts":[[2009]]}}}