@inproceedings{citeulike:1857323,
        title = {New methods for relevance feedback: improving information retrieval performance},
        address = {New York, NY, USA},
        author = {Paul V. Biron and Donald H. Kraft},
        booktitle = {SAC '95: Proceedings of the 1995 ACM symposium on Applied computing},
        pages = {482--487},
        publisher = {ACM},
        year = 1995,
        url = {http://portal.acm.org/citation.cfm?id=316072},
        id = {1857323},
	priority = {2},
	isbn = {0897916581},
	at = {2007-11-02 20:47:56},
	doi = {10.1145/315891.316072},
	biburl = {http://www.bibsonomy.org/bibtex/276bb63b55aef5f7dde80a7a88e86e448/pprett},
	keywords = {genetic, algorithm, relevance connectionist, feedback, learning,}
}

@article{citeulike:2081299,
        title = {A test of genetic algorithms in relevance feedback},
        author = {Cristina Lopez-Pujalte and  Guerrero and Felix Anegon},
        journal = {Information Processing \& Management},
        month = {November},
        number = 6,
        pages = {793--805},
        volume = 38,
        year = 2002,
        url = {http://dx.doi.org/10.1016/S0306-4573(01)00061-9},
        id = {2081299},
	priority = {2},
	at = {2007-12-09 10:19:25},
	doi = {10.1016/S0306-4573(01)00061-9},
	biburl = {http://www.bibsonomy.org/bibtex/2e4790dafd748e3e27ff21514c5231236/pprett},
	keywords = {genetic, algorithm, relevance feedback,}
}

@article{citeulike:2081307,
        title = {Genetic algorithms in relevance feedback: a second test and new contributions},
        author = {Cristina Lopez-Pujalte and Vicente P. Guerrero-Bote and Felix de Moya-Anegon},
        journal = {Information Processing \& Management},
        month = {September},
        number = 5,
        pages = {669--687},
        volume = 39,
        year = 2003,
        url = {http://dx.doi.org/10.1016/S0306-4573(02)00044-4},
        id = {2081307},
	priority = {2},
	at = {2007-12-09 10:27:40},
	doi = {10.1016/S0306-4573(02)00044-4},
	abstract = {The present work is the continuation of an earlier study which reviewed the literature on relevance feedback genetic techniques that follow the vector space model (the model that is most commonly used in this type of application), and implemented them so that they could be compared with each other as well as with one of the best traditional methods of relevance feedback--the Ide dec-hi method. We here carry out the comparisons on more test collections (Cranfield, CISI, Medline, and NPL), using the residual collection method for their evaluation as is recommended in this type of technique. We also add some fitness functions of our own design.},
	biburl = {http://www.bibsonomy.org/bibtex/283d2127533930fcb473277b3c8f5268f/pprett},
	keywords = {genetic, algorithm, relevance feedback,}
}