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% Encoding: Cp1252

@article{cooper,
 author = {Cooper, Gregory F. and Herskovits, Edward},
 title = {A Bayesian Method for the Induction of Probabilistic Networks from Data},
 journal = {Mach. Learn.},
 issue_date = {Oct. 1992},
 volume = {9},
 number = {4},
 month = oct,
 year = {1992},
 issn = {0885-6125},
 pages = {309--347},
 numpages = {39},
 url = {http://dx.doi.org/10.1023/A:1022649401552},
 doi = {10.1023/A:1022649401552},
 acmid = {145259},
 publisher = {Kluwer Academic Publishers},
 address = {Hingham, MA, USA},
 keywords = {Bayesian belief networks, induction, machine learning, probabilistic networks},
} 

@incollection{Robinson1977,
    abstract = {{The previously known ways to count acyclic digraphs, both labeled and unlabeled, are reviewed. Then a new method of enumerating unlabeled acyclic digraphs is developed. It involves computing the sum of the cyclic indices of the automorphism groups of the acyclic digraphs, achieving a considerable gain in efficiency through an application of the inclusion-exclusion principle. Numerical results are reported on, and a table of the numbers of unlabeled acyclic digraphs on up to 18 points is included.}},
    author = {Robinson, R. W.},
    booktitle = {Combinatorial Mathematics V},
    chapter = {2},
    citeulike-article-id = {8426666},
    citeulike-linkout-0 = {http://dx.doi.org/10.1007/bfb0069178},
    citeulike-linkout-1 = {http://www.springerlink.com/content/1716582847315l87},
    citeulike-linkout-2 = {http://link.springer.com/chapter/10.1007/BFb0069178},
    doi = {10.1007/bfb0069178},
    editor = {Little, CharlesH},
    isbn = {978-3-540-08524-9},
    keywords = {digraphs, directed-graphs, enumeration, graph-theory, work},
    pages = {28--43},
    posted-at = {2010-12-15 08:45:31},
    priority = {4},
    publisher = {Springer Berlin Heidelberg},
    series = {Lecture Notes in Mathematics},
    title = {{Counting unlabeled acyclic digraphs}},
    url = {http://dx.doi.org/10.1007/bfb0069178},
    volume = {622},
    year = {1977}
}

@book{Tan:2005:IDM:1095618,
 author = {Tan, Pang-Ning and Steinbach, Michael and Kumar, Vipin},
 title = {Introduction to Data Mining, (First Edition)},
 year = {2005},
 isbn = {0321321367},
 publisher = {Addison-Wesley Longman Publishing Co., Inc.},
 address = {USA},
}

@book{Jensen:2007:BNDG,
    author = {Jensen, Finn V. and Nielsen, Thomas D.},
    title = {Bayesian Networks and Decision Graphs},
    year = {2007},
    isbn = {9780387682815},
    edition = {2nd},
    publisher = {Springer Publishing Company, Incorporated},
}

@Article{Hoeffding:1963,
  author =       "Hoeffding, Wassily",
  title =        "Probability Inequalities for Sums of Bounded Random Variables",
  journal =      "Journal of the American Statistical Association",
  year =         "1963",
  pages =     "13--30",
}

@INCOLLECTION{Furnkranz:2011,
  author = {F{\"{u}}rnkranz, Johannes and H{\"{u}}llermeier, Eyke},
  title = {Preference Learning},
  publisher = {Springer},
  year = {2011}
}

@INPROCEEDINGS{CS01,
  author = {Koby Crammer and Yoram Singer},
  title = {Pranking with Ranking},
  booktitle = {{Proceedings of the 2001
Neural Information Processing Systems Conference (NIPS 2001)}},
  year = {2001},
  pages = {641-647},
  bibsource = {DBLP, http://dblp.uni-trier.de},
  ee = {http://www-2.cs.cmu.edu/Groups/NIPS/NIPS2001/papers/psgz/AA65.ps.gz},
  timestamp = {2013.06.01}, 
  address = {Vancouver, Canada}
}

@INPROCEEDINGS{Abdullah:2011:ICF:2117693.2119589,
  author = {Abdullah, Noraswaliza and Xu, Yue and Geva, Shlomo},
  title = {Integrating Collaborative Filtering and Search-Based Techniques for
	Personalized Online Product Recommendation},
  booktitle = {Proceedings of the 2011 IEEE 11th International Conference on Data
	Mining Workshops},
  year = {2011},
  series = {ICDMW '11},
  pages = {711--718},
  address = {Washington, DC, USA},
  publisher = {IEEE Computer Society},
  acmid = {2119589},
  doi = {10.1109/ICDMW.2011.102},
  isbn = {978-0-7695-4409-0},
  keywords = {recommender system, collaborative filtering, search-based technique,
	personalization},
  numpages = {8},
  url = {http://dx.doi.org/10.1109/ICDMW.2011.102}
}

@inproceedings{ictai2012,
 author = {Amo, Sandra de and Bueno, Marcos L. P. and Alves, Guilherme and Silva, Nadia F.},
 title = {{CPrefMiner}: An Algorithm for Mining User Contextual Preferences Based on Bayesian Networks},
 booktitle = {Proceedings of the 2012 IEEE 24th International Conference on Tools with Artificial Intelligence},
 series = {ICTAI '12},
 year = {2012},
 isbn = {978-0-7695-4915-6},
 pages = {114--121},
 numpages = {8},
 url = {http://dx.doi.org/10.1109/ICTAI.2012.24},
 doi = {10.1109/ICTAI.2012.24},
 acmid = {2455434},
 address = {Washington, DC, USA},
 keywords = {data mining, preference learning, genetic programming, bayesian networks},
}

@INPROCEEDINGS{deAmo:2012:MCP:2402140.2402166,
  author = {de Amo, Sandra and Diallo, Mouhamadou Saliou and Diop, Cheikh Talibouya
	and Giacometti, Arnaud and Li, Haoyuan D. and Soulet, Arnaud},
  title = {Mining contextual preference rules for building user profiles},
  booktitle = {Proceedings of the 14th international conference on Data Warehousing
	and Knowledge Discovery},
  year = {2012},
  series = {DaWaK'12},
  pages = {229--242},
  address = {Berlin, Heidelberg},
  publisher = {Springer-Verlag},
  acmid = {2402166},
  doi = {10.1007/978-3-642-32584-7_19},
  isbn = {978-3-642-32583-0},
  location = {Vienna, Austria},
  numpages = {14},
  url = {http://dx.doi.org/10.1007/978-3-642-32584-7_19}
}

@INPROCEEDINGS{conf:nips:BachM10,
  author = {Bach, Stephen H. and Maloof, Marcus A.},
  title = {A Bayesian Approach to Concept Drift.},
  booktitle = {NIPS},
  year = {2010},
  editor = {Lafferty, John D. and Williams, Christopher K. I. and Shawe-Taylor,
	John and Zemel, Richard S. and Culotta, Aron},
  pages = {127-135},
  publisher = {Curran Associates, Inc.},
  added-at = {2011-11-14T00:00:00.000+0100},
  biburl = {http://www.bibsonomy.org/bibtex/262786d79ae2391c0c02c24741728e43a/dblp},
  ee = {http://books.nips.cc/papers/files/nips23/NIPS2010_1334.pdf},
  interhash = {dcf91b36f5240dc2c39bd90508314a6d},
  intrahash = {62786d79ae2391c0c02c24741728e43a},
  keywords = {dblp},
  timestamp = {2011-11-14T00:00:00.000+0100},
  url = {http://dblp.uni-trier.de/db/conf/nips/nips2010.html#BachM10}
}

@ARTICLE{10.1109:DEXA.2011.52,
  author = {Davide Beretta and Elisa Quintarelli and Emanuele Rabosio},
  title = {Mining Context-Aware Preferences on Relational and Sensor Data},
  journal = {2012 23rd International Workshop on Database and Expert Systems Applications},
  year = {2011},
  volume = {0},
  pages = {116-120},
  address = {Los Alamitos, CA, USA},
  doi = {http://doi.ieeecomputersociety.org/10.1109/DEXA.2011.52},
  issn = {1529-4188},
  publisher = {IEEE Computer Society}
}

@PHDTHESIS{Bifet:2009:ALM:1656274.1656287,
  author = {Bifet, Albert},
  title = {Adaptive learning and mining for data streams and frequent patterns},
  school = {Universitat Politècnica de Catalunya},
  year = {2009}
}

@INPROCEEDINGS{Bifet07learningfrom,
  author = {Albert Bifet and Ricard Gavaldà},
  title = {Learning from time-changing data with adaptive windowing},
  booktitle = {In SIAM International Conference on Data Mining},
  year = {2007}
}

@article{Bifet:2010:MMO:1756006.1859903,
 author = {Bifet, Albert and Holmes, Geoff and Kirkby, Richard and Pfahringer, Bernhard},
 title = {{MOA: Massive Online Analysis}},
 journal = {J. Mach. Learn. Res.},
 issue_date = {3/1/2010},
 volume = {11},
 year = {2010},
 issn = {1532-4435},
 pages = {1601--1604},
 numpages = {4},
 url = {http://dl.acm.org/citation.cfm?id=1756006.1859903},
 acmid = {1859903},
}

@INPROCEEDINGS{Bifet:2010:LBE:1888258.1888275,
  author = {Bifet, Albert and Holmes, Geoff and Pfahringer, Bernhard},
  title = {Leveraging bagging for evolving data streams},
  booktitle = {Proceedings of the 2010 European conference on Machine learning and
	knowledge discovery in databases: Part I},
  year = {2010},
  series = {ECML PKDD'10},
  pages = {135--150},
  address = {Berlin, Heidelberg},
  publisher = {Springer-Verlag},
  acmid = {1888275},
  isbn = {3-642-15879-X, 978-3-642-15879-7},
  location = {Barcelona, Spain},
  numpages = {16},
  url = {http://dl.acm.org/citation.cfm?id=1888258.1888275}
}

@INPROCEEDINGS{Bifet:2009:NEM:1557019.1557041,
  author = {Bifet, Albert and Holmes, Geoff and Pfahringer, Bernhard and Kirkby,
	Richard and Gavald\`{a}, Ricard},
  title = {New ensemble methods for evolving data streams},
  booktitle = {Proceedings of the 15th ACM SIGKDD international conference on Knowledge
	discovery and data mining},
  year = {2009},
  series = {KDD '09},
  pages = {139--148},
  address = {New York, NY, USA},
  publisher = {ACM},
  acmid = {1557041},
  doi = {10.1145/1557019.1557041},
  isbn = {978-1-60558-495-9},
  keywords = {concept drift, data streams, decision trees, ensemble methods},
  location = {Paris, France},
  numpages = {10},
  url = {http://doi.acm.org/10.1145/1557019.1557041}
}

@techreport{citeulike:7359992,
    author = {Bifet, Albert and Kirkby, Richard},
    citeulike-article-id = {7359992},
    institution = {The University of Waikato},
    keywords = {concept, data, drift, learning, machine, mining},
    posted-at = {2010-06-26 09:39:10},
    priority = {0},
    title = {Data stream mining: a practical approach},
    year = {2009}
}

@MASTERSTHESIS{BrzezMs2010,
  author = {Dariusz Brzezinski},
  title = {Mining Data Streams with Concept Drift},
  school = {Poznan University of Technology},
  year = {2010},
  url = {http://www.cs.put.poznan.pl/dbrzezinski/publications/ConceptDrift.pdf}
}

@INPROCEEDINGS{Cohen:1998:LOT:302528.302736,
  author = {Cohen, William W. and Schapire, Robert E. and Singer, Yoram},
  title = {Learning to order things},
  booktitle = {Conference on Advances in Neural Information
	Processing Systems 10},
  year = {1998},
  pages = {451--457},
  acmid = {302736},
  isbn = {0-262-10076-2},
  numpages = {7},
}

@INPROCEEDINGS{Delgado:99,
  author = {Delgado, J. and Ishii, N.},
  title = {On-line learning of user preferences in recommender systems},
  booktitle = {International Joint Conference on Artificial Intelligence (IJCAI-99)},
  year = {1999},
}

@INPROCEEDINGS{Domingos:2000:MHD:347090.347107,
  author = {Domingos, Pedro and Hulten, Geoff},
  title = {Mining high-speed data streams},
  booktitle = {Proceedings of the sixth ACM SIGKDD international conference on Knowledge
	discovery and data mining},
  year = {2000},
  series = {KDD '00},
  pages = {71--80},
  address = {NY, USA},
  acmid = {347107},
  doi = {10.1145/347090.347107},
  isbn = {1-58113-233-6},
  keywords = {Hoeffding bounds, decision trees, disk-based algorithms, incremental
	learning, subsampling},
  location = {Boston, Massachusetts, United States},
  numpages = {10},
  url = {http://doi.acm.org/10.1145/347090.347107}
}

@ARTICLE{Freund:2003:EBA:945365.964285,
  author = {Freund, Yoav and Iyer, Raj and Schapire, Robert E. and Singer, Yoram},
  title = {An efficient boosting algorithm for combining preferences},
  journal = {J. Mach. Learn. Res.},
  year = {2003},
  volume = {4},
  pages = {933--969},
  acmid = {964285},
  issn = {1532-4435},
  issue_date = {12/1/2003},
  numpages = {37},
  publisher = {JMLR.org},
  url = {http://dl.acm.org/citation.cfm?id=945365.964285}
}

@INCOLLECTION{plbook:Introduction,
  author = {F{\"{u}}rnkranz, Johannes and H{\"{u}}llermeier, Eyke},
  title = {Preference Learning: An Introduction},
  booktitle = {Preference Learning},
  publisher = {Springer-Verlag},
  year = {2010},
  editor = {F{\"{u}}rnkranz, Johannes and H{\"{u}}llermeier, Eyke},
  pages = {1--17},
  url = {http://www.ke.informatik.tu-darmstadt.de/publications/papers/PLBook-Introduction.pdf}
}

@ARTICLE{Gaber:2005:MDS:1083784.1083789,
  author = {Gaber, Mohamed Medhat and Zaslavsky, Arkady and Krishnaswamy, Shonali},
  title = {Mining data streams: a review},
  journal = {SIGMOD Rec.},
  year = {2005},
  volume = {34},
  pages = {18--26},
  number = {2},
  month = jun,
  acmid = {1083789},
  address = {New York, NY, USA},
  doi = {10.1145/1083784.1083789},
  issn = {0163-5808},
  issue_date = {June 2005},
  numpages = {9},
  publisher = {ACM},
  url = {http://doi.acm.org/10.1145/1083784.1083789}
}

@BOOK{Gama:2010:KDD:1855075,
  title = {Knowledge Discovery from Data Streams},
  publisher = {Chapman \& Hall/CRC},
  year = {2010},
  author = {Gama, Joao},
  edition = {1st},
  isbn = {1439826110, 9781439826119}
}

@CONFERENCE{Grbovic:2012,
  author = {Grbovic, M. and Djuric, N. and Vucetic, S.},
  title = {Learning from Pairwise Preference Data using Gaussian Mixture Model},
  booktitle = {Preference Learning Workshop, European Conference on Artificial Intelligence
	(ECAI)},
  year = {2012}
}

@INPROCEEDINGS{Holland2003,
  author = {Holland, Stefan and Ester, Martin and Kie{\ss}ling, Werner},
  title = {Preference Mining: A Novel Approach on Mining User Preferences for
	Personalized Applications},
  year = {2003},
  booktitle = {PKDD},
  publisher = {Springer},
}

@inproceedings{Jembere:2007:MCU:1331740.1331819,
 author = {Jembere, E and Adigun, M. O. and Xulu, S. S.},
 title = {Mining Context-based User Preferences for m-Services Applications},
 booktitle = {Proceedings of the IEEE/WIC/ACM International Conference on Web Intelligence},
 series = {WI '07},
 year = {2007},
 isbn = {0-7695-3026-5},
 pages = {757--763},
 numpages = {7},
 url = {http://dx.doi.org/10.1109/WI.2007.141},
 doi = {10.1109/WI.2007.141},
 acmid = {1331819},
 address = {Washington, DC, USA},
}

@BOOK{Jensen:2007:BND:1535531,
  title = {Bayesian Networks and Decision Graphs},
  publisher = {Springer Publishing Company, Incorporated},
  year = {2007},
  author = {Jensen, Finn V. and Nielsen, Thomas D.},
  edition = {2nd},
  isbn = {9780387682815}
}

@inproceedings{Jiang:2008:MPS:1401890.1401940,
 author = {Jiang, Bin and Pei, Jian and Lin, Xuemin and Cheung, David W. and Han, Jiawei},
 title = {Mining preferences from superior and inferior examples},
 booktitle = {Proceedings of the 14th ACM SIGKDD international conference on Knowledge discovery and data mining},
 series = {KDD '08},
 year = {2008},
 isbn = {978-1-60558-193-4},
 location = {Las Vegas, Nevada, USA},
 pages = {390--398},
 numpages = {9},
 url = {http://doi.acm.org/10.1145/1401890.1401940},
 doi = {10.1145/1401890.1401940},
 acmid = {1401940},
 address = {New York, NY, USA},
 keywords = {inferior examples, preferences, skyline, superior examples}
}

@INPROCEEDINGS{Kontaki:2009:CPP:1697085.1697090,
  author = {Kontaki, Maria and Papadopoulos, Apostolos N. and Manolopoulos, Yannis},
  title = {Continuous Processing of Preference Queries in Data Streams},
  booktitle = {Proceedings of the 36th Conference on Current Trends in Theory and
	Practice of Computer Science},
  year = {2010},
  series = {SOFSEM '10},
  pages = {47--60},
  address = {Berlin, Heidelberg},
  publisher = {Springer-Verlag},
  acmid = {1697090},
  doi = {10.1007/978-3-642-11266-9_4},
  isbn = {978-3-642-11265-2},
  location = {`pindlerov Ml\&\#253;n, Czech Republic},
  numpages = {14},
  url = {http://dx.doi.org/10.1007/978-3-642-11266-9_4}
}

@ARTICLE{Kramer:2009:SIC:1508857.1508861,
  author = {Kr\"{a}mer, J\"{u}rgen and Seeger, Bernhard},
  title = {Semantics and implementation of continuous sliding window queries
	over data streams},
  journal = {ACM Trans. Database Syst.},
  year = {2009},
  volume = {34},
  pages = {4:1--4:49},
  number = {1},
  month = apr,
  acmid = {1508861},
  address = {New York, NY, USA},
  articleno = {4},
  doi = {10.1145/1508857.1508861},
  issn = {0362-5915},
  issue_date = {April 2009},
  keywords = {Semantics, continuous queries, data streams, query optimization},
  numpages = {49},
  publisher = {ACM},
  url = {http://doi.acm.org/10.1145/1508857.1508861}
}

@ARTICLE{Krause:2006:CMC:1107312.1107346,
  author = {Krause, Andreas and Smailagic, Asim and Siewiorek, Daniel P.},
  title = {Context-Aware Mobile Computing: Learning Context-Dependent Personal
	Preferences from a Wearable Sensor Array},
  journal = {IEEE Transactions on Mobile Computing},
  year = {2006},
  volume = {5},
  pages = {113--127},
  number = {2},
  month = feb,
  acmid = {1107346},
  address = {Piscataway, NJ, USA},
  doi = {10.1109/TMC.2006.18},
  issn = {1536-1233},
  issue_date = {February 2006},
  keywords = {Index Terms- Location-dependent and sensitive, Index Terms- Location-dependent
	and sensitive, wearable computers, mobile computing, machine learning,
	wearable AI, statistical models., machine learning, mobile computing,
	statistical models., wearable AI, wearable computers},
  numpages = {15},
  publisher = {IEEE Educational Activities Department},
  url = {http://dx.doi.org/10.1109/TMC.2006.18}
}

@ARTICLE{Morse:2007:ECS:1269987.1270106,
  author = {Morse, M. and Patel, J. M. and Grosky, W. I.},
  title = {Efficient continuous skyline computation},
  journal = {Inf. Sci.},
  year = {2007},
  volume = {177},
  pages = {3411--3437},
  number = {17},
  month = sep,
  acmid = {1270106},
  address = {New York, NY, USA},
  doi = {10.1016/j.ins.2007.02.033},
  issn = {0020-0255},
  issue_date = {September, 2007},
  keywords = {Algorithm, Database, Index, Multidimensional data structures, Quadtree,
	R<sup>*</sup>-tree, Skyline},
  numpages = {27},
  publisher = {Elsevier Science Inc.},
  url = {http://dx.doi.org/10.1016/j.ins.2007.02.033}
}

@INPROCEEDINGS{Oza01onlinebagging,
  author = {Nikunj C. Oza and Stuart Russell},
  title = {Online Bagging and Boosting},
  booktitle = {In Artificial Intelligence and Statistics 2001},
  year = {2001},
  pages = {105--112},
  publisher = {Morgan Kaufmann}
}

@MASTERSTHESIS{Pinto:2005,
  author = {Pinto, C. M. S.},
  title = {Algoritmos Incrementais para Aprendizagem Bayesiana},
  school = {Universidade do Porto},
  year = {2005},
  owner = {Jaque},
  timestamp = {2013.01.25}
}

@INPROCEEDINGS{Pruhs:2011:GCA:2082752.2082915,
  author = {Pruhs, Kirk},
  title = {Green Computing Algorithmics},
  booktitle = {Proceedings of the 2011 IEEE 52nd Annual Symposium on Foundations
	of Computer Science},
  year = {2011},
  series = {FOCS '11},
  pages = {3--4},
  address = {Washington, DC, USA},
  publisher = {IEEE Computer Society},
  acmid = {2082915},
  doi = {10.1109/FOCS.2011.44},
  isbn = {978-0-7695-4571-4},
  numpages = {2},
  url = {http://dx.doi.org/10.1109/FOCS.2011.44}
}

@BOOK{massive2012,
  title = {Mining of Massive Datasets},
  publisher = {Cambridge University Press},
  year = {2011},
  author = {Rajaraman, Anand and Ullman, Jeffrey David},
  pages = {Chapter 4 - Mining Data Streams},
  address = {NY, USA},
  isbn = {1107015359, 9781107015357}
}

@ARTICLE{journals:corr:abs-1111-0712,
  author    = {Pannagadatta K. Shivaswamy and
               Thorsten Joachims},
  title     = {Online Learning with Preference Feedback},
  journal   = {CoRR},
  volume    = {abs/1111.0712},
  year      = {2011},
  ee        = {http://arxiv.org/abs/1111.0712},
  bibsource = {DBLP, http://dblp.uni-trier.de},
  pages = {1--5},
}

@INPROCEEDINGS{Somefun:2004:OLA:1052220.1052266,
  author = {Somefun, D. J. A. and Klos, T. B. and La Poutr{\'e}, J. A.},
  title = {Online learning of aggregate knowledge about non-linear preferences
	applied to negotiating prices and bundles},
  booktitle = {Proceedings of the 6th international conference on Electronic commerce},
  year = {2004}
}

@inproceedings{Somefun:2006:FML:1758730.1758739,
 author = {Somefun, D. J. A. and La Poutr{\'e}, J. A.},
 title = {A fast method for learning non-linear preferences online using anonymous negotiation data},
 booktitle = {Proceedings of the 2006 AAMAS workshop and TADA/AMEC 2006 conference on Agent-mediated electronic commerce},
 series = {TADA/AMEC'06},
 year = {2007},
 isbn = {978-3-540-72501-5},
 location = {Hakodate, Japan},
 pages = {118--131},
 numpages = {14},
 url = {http://dl.acm.org/citation.cfm?id=1758730.1758739},
 acmid = {1758739},
 address = {Berlin, Heidelberg},
 publisher = {Springer}
}

@INPROCEEDINGS{Somefun:2006:SMO:1160633.1160707,
  author = {Somefun, D. J. A. and La Poutr{\'e}, J. A.},
  title = {A scalable method for online learning of non-linear preferences based
	on anonymous negotiation data},
  booktitle = {Proceedings of the fifth international joint conference on Autonomous
	agents and multiagent systems},
  year = {2006},
  series = {AAMAS '06},
  pages = {417--419},
  address = {New York, NY, USA},
  publisher = {ACM},
  acmid = {1160707},
  doi = {10.1145/1160633.1160707},
  isbn = {1-59593-303-4},
  keywords = {market-based methods, negotiation, online learning},
  location = {Hakodate, Japan},
  numpages = {3},
  url = {http://doi.acm.org/10.1145/1160633.1160707}
}

@TECHREPORT{Tsymbal:2004,
  author = {Tsymbal, Alexey},
  title = {The problem of concept drift: definitions and related work},
  institution = {The University of Dublin, Trinity College, Department of Computer
	Science},
  year = {2004},
  number = {TCD-CS-2004-15},
  address = {Dublin, Ireland},
  abstract = {In the real world concepts are often not stable but change with time.
	Typical examples of this are weather prediction rules and customers?
	preferences. The underlying data distribution may change as well.
	Often these changes make the model built on old data inconsistent
	with the new data, and regular updating of the model is necessary.
	This problem, known as concept drift, complicates the task of learning
	a model from data and requires special approaches, different from
	commonly used techniques, which treat arriving instances as equally
	important contributors to the final concept. This paper considers
	different types of concept drift, peculiarities of the problem, and
	gives a critical review of existing approaches to the problem.},
  added-at = {2009-06-26T15:25:19.000+0200},
  biburl = {http://www.bibsonomy.org/bibtex/2dab086e0bb0ced9dc0f65f6368ff8cea/butz},
  description = {diverse cognitive systems bib},
  interhash = {4689849554541fb8940e561856487d3d},
  intrahash = {dab086e0bb0ced9dc0f65f6368ff8cea},
  keywords = {imported},
  owner = {butz},
  timestamp = {2009-06-26T15:25:19.000+0200}
}

@article{Vivekanandan:2011:MDS:2036659.2036682,
 author = {Vivekanandan, Periasamy and Nedunchezhian, Raju},
 title = {Mining data streams with concept drifts using genetic algorithm},
 journal = {Artif. Intell. Rev.},
 issue_date = {October   2011},
 volume = {36},
 number = {3},
 year = {2011},
 issn = {0269-2821},
 pages = {163--178},
 numpages = {16},
 url = {http://dx.doi.org/10.1007/s10462-011-9209-y},
 doi = {10.1007/s10462-011-9209-y},
 acmid = {2036682},
 address = {Norwell, MA, USA},
 keywords = {Classification, Concept drift, Genetic algorithm (GA), Online learning},
}

@inproceedings{wilson2004,
 author = {Wilson, Nic},
 title = {Extending CP-nets with stronger conditional preference statements},
 booktitle = {Proceedings of the 19th national conference on Artifical intelligence},
 series = {AAAI'04},
 year = {2004},
 isbn = {0-262-51183-5},
 location = {San Jose, California},
 pages = {735--741},
 numpages = {7},
 url = {http://dl.acm.org/citation.cfm?id=1597148.1597266},
 acmid = {1597266}
}

@BOOK{Yong:2012,
  title = {Bio-Inspired Computational Algorithms and Their Applications},
  publisher = {InTech},
  year = {2012},
  author = {Yong, Zhou and Jun, Han and He, Guo},
  pages = {Mining Frequent Itemsets over Recent Data Stream Based on Genetic
	Algorithm},
  doi = {10.5772/38445},
  isbn = {9789535102144},
  url = {http://www.intechopen.com/books/bio-inspiredcomputational-algorithms-and-their-applications/mining-frequent-itemsets-over-recent-data-stream-based-ongenetic-algorithm}
}
