@article{BaniassadEtAl2006.ieee,
	title = {Discovering Early Aspects},
	author = {Elisa Baniassad and Paul C. Clements and Joao Araujo and Ana Moreira and Awais Rashid and Bedir Tekinerdogan},
	journal = {IEEE Software},
	month = {January-February},
	number = {1},
	pages = {61--70},
	volume = {23},
	year = {2006},
	biburl = {http://www.bibsonomy.org/bibtex/2b370efcc99d15ac7905e6bd95bf2a358/pdeleenh},
	timestamp = {2008.05.15}, date-modified = {2007-09-26 10:31:35 +0200}, owner = {pdeleenh},
	keywords = {aspects }
}

@inproceedings{conf/fuzzIEEE/AraujoC07,
	title = {Fuzzy Model and Particle Swarm Optimization for Nonlinear Identification of a Chua's Oscillator.},
	author = {Ernesto Araujo and Leandro dos Santos Coelho},
	booktitle = {FUZZ-IEEE},
	crossref = {conf/fuzzIEEE/2007},
	pages = {1-6},
	publisher = {IEEE},
	url = {http://dblp.uni-trier.de/db/conf/fuzzIEEE/fuzzIEEE2007.html#AraujoC07},
	year = {2007},
	biburl = {http://www.bibsonomy.org/bibtex/2e80fa543eaf841111b8236404a87cbf9/dblp},
	description = {dblp},
	ee = {http://dx.doi.org/10.1109/FUZZY.2007.4295644}, date = {2008-07-04},
	keywords = {dblp }
}

@inproceedings{conf/visapp/LebonvalletKR07,
	title = {Automated tumor segmentation using level set methods.},
	author = {Stéphane Lebonvallet and Sonia Khatchadourian and Su Ruan},
	booktitle = {VISAPP (Special Sessions)},
	crossref = {conf/visapp/2007-ss},
	editor = {Alpesh Ranchordas and Helder Araújo and Jordi Vitrià},
	pages = {128-133},
	publisher = {INSTICC - Institute for Systems and Technologies of Information, Control and Communication},
	url = {http://dblp.uni-trier.de/db/conf/visapp/visapp2007-ss.html#LebonvalletKR07},
	year = {2007},
	biburl = {http://www.bibsonomy.org/bibtex/26cb12f98110481440f32eadd8017b8d7/dblp},
	description = {dblp},
	isbn = {978-972-8865-75-7}, date = {2008-07-03},
	keywords = {dblp }
}

@article{journals/corr/abs-0806-2843,
	title = {MultiKulti Algorithm: Migrating the Most Different Genotypes in an Island Model},
	author = {Lourdes Araujo and Juan Julián Merelo Guervos and Carlos Cotta and Francisco Fernández de Vega},
	journal = {CoRR},
	note = {informal publication},
	url = {http://dblp.uni-trier.de/db/journals/corr/corr0806.html#abs-0806-2843},
	volume = {abs/0806.2843},
	year = {2008},
	biburl = {http://www.bibsonomy.org/bibtex/2e05874be321ead7e8a0b98093efabf20/dblp},
	description = {dblp},
	ee = {http://arxiv.org/abs/0806.2843}, date = {2008-07-02},
	keywords = {dblp }
}

@inproceedings{conf/nldb/Perez-AgueraZA08,
	title = {Exploiting Morphological Query Structure Using Genetic Optimisation.},
	author = {José R. Pérez-Agüera and Hugo Zaragoza and Lourdes Araujo},
	booktitle = {NLDB},
	crossref = {conf/nldb/2008},
	editor = {Epaminondas Kapetanios and Vijayan Sugumaran and Myra Spiliopoulou},
	pages = {124-135},
	publisher = {Springer},
	series = {Lecture Notes in Computer Science},
	url = {http://dblp.uni-trier.de/db/conf/nldb/nldb2008.html#Perez-AgueraZA08},
	volume = {5039},
	year = {2008},
	biburl = {http://www.bibsonomy.org/bibtex/2d2d42847e79bc3ca3c2cd59aec6a0a1d/dblp},
	description = {dblp},
	date = {2008-06-27}, ee = {http://dx.doi.org/10.1007/978-3-540-69858-6_13}, isbn = {978-3-540-69857-9},
	keywords = {dblp }
}

@inproceedings{Araujo:PPSN:2006,
	title = {Multiobjective Genetic Programming for Natural
                 Language Parsing and Tagging},
	address = {Reykjavik, Iceland},
	author = {L. Araujo},
	booktitle = {Parallel Problem Solving from Nature - PPSN IX},
	editor = {Thomas Philip Runarsson and Hans-Georg Beyer and Edmund Burke and Juan J. Merelo-Guervos and L. Darrell Whitley and Xin Yao},
	month = {9-13 September},
	pages = {433--442},
	publisher = {Springer-Verlag},
	series = {LNCS},
	url = {http://ppsn2006.raunvis.hi.is/proceedings/055.pdf},
	volume = {4193},
	year = {2006},
	biburl = {http://www.bibsonomy.org/bibtex/2f4cff8b1657301d45021ae719c2fa0d9/brazovayeye},
	abstract = {Parsing and Tagging are very important tasks in
                 Natural Language Processing. Parsing amounts to
                 searching the correct combination of grammatical rules
                 among those compatible with a given sentence. Tagging
                 amounts to labelling each word in a sentence with its
                 lexical category and, because many words belong to more
                 than one lexical class, it turns out to be a
                 disambiguation task. Because parsing and tagging are
                 related tasks, its simultaneous resolution can improve
                 the results of both of them. This work aims developing
                 a multiobjective genetic program to perform
                 simultaneously statistical parsing and tagging. It
                 combines the statistical data about grammar rules and
                 about tag sequences to guide the search of the best
                 structure. Results show that any of the implemented
                 multiobjective optimisation models improve on the
                 results obtained in the resolution of each problem
                 separately.},
	publisher_address = {Berlin}, size = {10 pages}, isbn = {3-540-38990-3}, notes = {PPSN-IX}, doi = {doi:10.1007/11844297_44},
	keywords = {algorithms, genetic programming }
}

@inproceedings{araujo:2004:eurogp,
	title = {Genetic Programming for Natural Language Parsing},
	address = {Coimbra, Portugal},
	author = {Lourdes Araujo},
	booktitle = {Genetic Programming 7th European Conference, EuroGP
                 2004, Proceedings},
	editor = {Maarten Keijzer and Una-May O'Reilly and Simon M. Lucas and Ernesto Costa and Terence Soule},
	month = {5-7 April},
	pages = {230--239},
	publisher = {Springer-Verlag},
	series = {LNCS},
	url = {http://www.springerlink.com/openurl.asp?genre=article&issn=0302-9743&volume=3003&spage=230},
	volume = {3003},
	year = {2004},
	biburl = {http://www.bibsonomy.org/bibtex/2df62f1aafeb52863e0c20d59e4b059ef/brazovayeye},
	abstract = {Our aim is to prove the effectiveness of the genetic
                 programming approach in automatic parsing of sentences
                 of real texts. Classical parsing methods are based on
                 complete search techniques to find the different
                 interpretations of a sentence. However, the size of the
                 search space increases exponentially with the length of
                 the sentence or text to be parsed and the size of the
                 grammar, so that exhaustive search methods can fail to
                 reach a solution in a reasonable time. This paper
                 presents the implementation of a probabilistic
                 bottom-up parser based on genetic programming which
                 works with a population of partial parses, i.e. parses
                 of sentence segments. The quality of the individuals is
                 computed as a measure of its probability, which is
                 obtained from the probability of the grammar rules and
                 lexical tags involved in the parse. In the approach
                 adopted herein, the size of the trees generated is
                 limited by the length of the sentence. In this way, the
                 size of the search space, determined by the size of the
                 sentence to parse, the number of valid lexical tags for
                 each words and specially by the size of the grammar, is
                 also limited.},
	organisation = {EvoNet}, publisher_address = {Berlin}, isbn = {3-540-21346-5}, notes = {Part of \cite{keijzer:2004:GP} EuroGP'2004 held in
                 conjunction with EvoCOP2004 and EvoWorkshops2004},
	keywords = {algorithms, genetic programming }
}

@inproceedings{semish2003meta007,
	title = {{S}{\'i}ntese de Circuitos Digitais Otimizados via
                 Programa{\c c}{\~a}o Gen{\'e}tica},
	address = {Unicamp, Campinas, SP, Brasil},
	author = {Sergio Granato {de Araujo} and Antonio C. Mesquita and Aloysio C. P. Pedroza},
	booktitle = {XXX Semin{\'a}rio Integrado de Software e Hardware},
	month = {2-8 August},
	url = {http://www.sbc.org.br/sbc2003_cd/pdf/arq0088.pdf
                 broken},
	year = {2003},
	biburl = {http://www.bibsonomy.org/bibtex/21f2136433946ba6da3d04e33d3d847d7/brazovayeye},
	abstract = {This paper presents a methodology for the design of
                 optimized electronic digital systems from high
                 abstraction level descriptions. The methodology uses
                 Genetic Programming in addition to high-level synthesis
                 tools to improve the design quality (area
                 optimization). A two-stage, multiobjective optimization
                 algorithm was used to search for circuits with the
                 desired functionality subjected additionally to chip
                 area constraints. Experiment with a square-root
                 approximation function design targeted to FPGA
                 illustrates the methodology.},
	rights = {Sociedade Brasileira de Computa{\c c}{\~a}o}, source = {semish2003}, language = {por; eng}, notes = {XXIII Brazilian Symposium on Computation (SBC'03)
                 http://www.ic.unicamp.br/sbc2003/enia.html

                 url broken 27 Sep 2004

                 In Portuguese

                 }, identifier = {semish2003article007},
	keywords = {algorithms, genetic programming }
}

@inproceedings{araujo:2003:ICES,
	title = {Using Genetic Programming and High Level Synthesis to
                 Design Optimized Datapath},
	address = {Trondheim, Norway},
	author = {Sergio G. Araujo and A. Mesquita and Aloysio C. P. Pedroza},
	booktitle = {Evolvable Systems: From Biology to Hardware, Fifth
                 International Conference, ICES 2003},
	editor = {Andy M. Tyrrell and Pauline C. Haddow and Jim Torresen},
	month = {17-20 March},
	pages = {434--445},
	publisher = {Springer-Verlag},
	series = {LNCS},
	url = {http://www.springer.de/cgi-bin/search_book.pl?isbn=3-540-00730-X},
	volume = {2606},
	year = {2003},
	biburl = {http://www.bibsonomy.org/bibtex/22cb020f2eee0f680e734e933abfd2726/brazovayeye},
	abstract = {a methodology to design optimised electronic digital
                 systems from high abstraction level descriptions. The
                 methodology uses Genetic Programming in addition to
                 high-level synthesis tools to automatically improve
                 design structural quality (area measure). A two-stage,
                 multiobjective optimization algorithm is used to search
                 for circuits with the desired functionality subjected
                 additionally to chip area constraints. Experiment with
                 a square-root approximation datapath design targeted to
                 FPGA exemplifies the proposed methodology.},
	isbn = {3-540-00730-X}, notes = {ICES-2003},
	keywords = {algorithms, genetic programming }
}

@inproceedings{araujo:2000:R,
	title = {Rule discovery with a parallel genetic algorithm},
	address = {Las Vegas, Nevada, USA},
	author = {Dieferson L. A. Araujo and Heitor S. Lopes and Alex A. Freitas},
	booktitle = {Data Mining with Evolutionary Algorithms},
	editor = {Alex A. Freitas and William Hart and Natalio Krasnogor and Jim Smith},
	month = {8 July},
	pages = {89--94},
	url = {http://www.cpgei.cefetpr.br/~hslopes/publicacoes/2000/gecco2000b.zip},
	year = {2000},
	biburl = {http://www.bibsonomy.org/bibtex/2041b63de1ff86e2a5496a85ee9ecf2ef/brazovayeye},
	notes = {GECCO-2000WKS Part of \cite{wu:2000:GECCOWKS}},
	keywords = {algorithms, data genetic mining, parallel }
}