@book{Rijsbergen1979,
	title = {Information Retrieval, 2nd edition},
	author = {C. J. Van Rijsbergen},
	edition = {Second},
	publisher = {Dept. of Computer Science, University of Glasgow},
	url = {http://www.dcs.gla.ac.uk/Keith/Preface.html},
	year = {1979},
	biburl = {http://www.bibsonomy.org/bibtex/2f3560b755944a90e1d55d2621ec45f22/chriskoerner},
	abstract = {Information retrieval is a wide, often loosely-defined term but in these pages I shall be concerned only with automatic information retrieval systems. Automatic as opposed to manual and information as opposed to data or fact. Unfortunately the word information can be very misleading. In the context of information retrieval (IR), information, in the technical meaning given in Shannon's theory of communication, is not readily measured (Shannon and Weaver1). In fact, in many cases one can...},
	keywords = {informationretrieval similarity }
}

@article{citeulike:969264,
	title = {Evaluating implicit feedback models using searcher simulations},
	address = {New York, NY, USA},
	author = {Ryen W. White and Ian Ruthven and Joemon M. Jose and Cornelis J. van Rijsbergen},
	journal = {ACM Trans. Inf. Syst.},
	month = {July},
	number = {3},
	pages = {325--361},
	publisher = {ACM Press},
	url = {http://portal.acm.org/citation.cfm?id=1080343.1080347},
	volume = {23},
	year = {2005},
	biburl = {http://www.bibsonomy.org/bibtex/295d9a9220a3a49446e236b38508faa6f/pprett},
	issn = {1046-8188}, posted-at = {2007-10-01 13:37:33}, citeulike-article-id = {969264}, priority = {2}, doi = {10.1145/1080343.1080347},
	keywords = {evaluation, feedback, implicit, information, model, relevance, retrieval }
}

@article{citeulike:397741,
	title = {Incorporating user search behavior into relevance feedback},
	author = {Ian Ruthven and Mounia Lalmas and Keith van Rijsbergen},
	journal = {Journal of the American Society for Information Science and Technology},
	month = {February},
	number = {6},
	pages = {529--549},
	url = {http://portal.acm.org/citation.cfm?id=779042.779049},
	volume = {54},
	year = {2003},
	biburl = {http://www.bibsonomy.org/bibtex/26de847b6e5355da09644ec68fca8beeb/pprett},
	abstract = {In this paper, we present five user experiments on incorporating behavioral information into the relevance feedback process. In particular, we concentrate on ranking terms for query expansion and selecting new terms to add to the user's query. Our experiments are an attempt to widen the evidence used for relevance feedback from simply the relevant documents to include information on how users are searching. We show that this information can lead to more successful relevance feedback techniques. We also show that the presentation of relevance feedback to the user is important in the success of relevance feedback.},
	issn = {1532-2890}, posted-at = {2007-10-01 13:44:33}, citeulike-article-id = {397741}, priority = {4}, doi = {10.1002/asi.10240},
	keywords = {behavior, evaluation, feedback, query, reformulating, relevance, search, user }
}

@book{rijsbergen04geometry,
	title = {The Geometry of Information Retrieval},
	author = {C. J. van Rijsbergen},
	howpublished = {Hardcover},
	month = {August},
	publisher = {Cambridge University Press},
	url = {http://www.amazon.ca/exec/obidos/redirect?tag=citeulike09-20\&path=ASIN/0521838053},
	year = {2004},
	biburl = {http://www.bibsonomy.org/bibtex/28010ff2de2e6dba8b90f65ffbf624567/pprett},
	abstract = {Keith Van Rijsbergen demonstrates how different models of information retrieval (IR) can be combined in the same framework used to formulate the general principles of quantum mechanics. All the standard results can be applied to address problems in IR, such as pseudo-relevance feedback, relevance feedback and ostensive retrieval. The relation with quantum computing is examined. Appendices with background material on physics and mathematics are also included.},
	posted-at = {2007-10-16 09:03:43}, citeulike-article-id = {111663}, priority = {2}, isbn = {0521838053},
	keywords = {information, ir, retrieval, theoretical }
}

@article{citeulike:1884740,
	title = {Probabilistic models of information retrieval based on measuring the divergence from randomness},
	address = {New York, NY, USA},
	author = {Gianni Amati and Cornelis J. van Rijsbergen},
	journal = {ACM Trans. Inf. Syst.},
	month = {October},
	number = {4},
	pages = {357--389},
	publisher = {ACM},
	url = {http://portal.acm.org/citation.cfm?id=582416},
	volume = {20},
	year = {2002},
	biburl = {http://www.bibsonomy.org/bibtex/28392d2cf9ee43364f0fd133b9cb6525a/pprett},
	issn = {1046-8188}, posted-at = {2007-11-08 13:12:07}, citeulike-article-id = {1884740}, priority = {3}, doi = {10.1145/582415.582416},
	keywords = {dfr, information, model, probabilistic, retrieval }
}

@misc{citeulike:1894931,
	title = {Is this document relevant?...Probably: A survey of probabilistic models in information retrieval},
	author = {F. Crestani and M. Lalmas and Cornelis J. van Rijsbergen and I. Campbell},
	url = {http://citeseer.ist.psu.edu/540498.html},
	year = {1998},
	biburl = {http://www.bibsonomy.org/bibtex/2e864d72a552aaaf67f56d4f4502d5d1f/pprett},
	abstract = {This article surveys probabilistic approaches to modeling information retrieval. The basic concepts of probabilistic approaches to information retrieval are outlined and the principles and assumptions upon which the approaches are based are presented. The various models proposed in the development of IR are described, classified, and compared using a common formalism. New approaches that constitute the basis of future research are described},
	posted-at = {2007-11-10 16:42:58}, priority = {4}, citeulike-article-id = {1894931},
	keywords = {information, model, probabilistic, retrieval, survey }
}

@inproceedings{citeulike:1369124,
	title = {Boosting and Rocchio applied to text filtering},
	address = {Melbourne, AU},
	author = {Robert E. Schapire and Yoram Singer and Amit Singhal},
	booktitle = {Proceedings of SIGIR-98, 21st ACM International Conference on Research and Development in Information Retrieval},
	editor = {Bruce W. Croft and Alistair Moffat and Cornelis J. van Rijsbergen and Ross Wilkinson and Justin Zobel},
	pages = {215--223},
	publisher = {ACM Press, New York, US},
	url = {http://citeseer.ist.psu.edu/schapire98boosting.html},
	year = {1998},
	biburl = {http://www.bibsonomy.org/bibtex/2d1bcc20efbb28e33012cb22fc53b0787/pprett},
	abstract = {We discuss two learning algorithms for text filtering: modified Rocchio and a boosting algorithm called AdaBoost. We show how both algorithms can be adapted to maximize any general utility matrix that associates cost (or gain) for each pair of machine prediction and correct label. We first show that AdaBoost significantly outperforms another highly effective text filtering algorithm. We then compare AdaBoost and Rocchio over three large text filtering tasks. Overall both algorithms are...},
	posted-at = {2008-02-21 20:10:24}, citeulike-article-id = {1369124}, priority = {4},
	keywords = {boosting, filtering, information, rocchio }
}

@article{citeulike:1789087,
	title = {A Model for Adaptive Information Retrieval},
	author = {Fabio Crestani and Cornelis J. van Rijsbergen},
	journal = {Journal of Intelligent Information Systems},
	month = {January},
	number = {1},
	pages = {29--56},
	url = {http://dx.doi.org/10.1023/A:1008601616486},
	volume = {8},
	year = {1997},
	biburl = {http://www.bibsonomy.org/bibtex/291eb586089467fbdbf75c8418de1c167/pprett},
	abstract = {The paper presents a network model that can be used toproduce conceptual and logical schemas for Information Retrievalapplications. The model has interesting adaptability characteristicsand can be instantiated in various effective ways. The paper alsoreports the results of an experimental investigation into theeffectiveness of implementing associative and adaptive retrieval onthe proposed model by means of Neural Networks. The implementationmakes use of the learning and generalisation capabilities of theBackpropagation learning algorithm to build up and use applicationdomain knowledge in a sub-symbolic form. The knowledge is acquiredfrom examples of queries and relevant documents. Three differentlearning strategies are introduced, their performance is analysed andcompared with the performance of a traditional Information Retrievalsystem.},
	posted-at = {2008-03-19 09:13:05}, citeulike-article-id = {1789087}, priority = {2}, doi = {10.1023/A:1008601616486},
	keywords = {adaptive, ann, ir, sa }
}

@book{citeulike:543360,
	title = {Information Retrieval, 2nd edition},
	author = {C. J. Van Rijsbergen},
	publisher = {Dept. of Computer Science, University of Glasgow},
	url = {http://citeseer.ist.psu.edu/vanrijsbergen79information.html},
	year = {1979},
	biburl = {http://www.bibsonomy.org/bibtex/2f3560b755944a90e1d55d2621ec45f22/pprett},
	abstract = {Information retrieval is a wide, often loosely-defined term but in these pages I shall be concerned only with automatic information retrieval systems. Automatic as opposed to manual and information as opposed to data or fact. Unfortunately the word information can be very misleading. In the context of information retrieval (IR), information, in the technical meaning given in Shannon's theory of communication, is not readily measured (Shannon and Weaver1). In fact, in many cases one can...},
	posted-at = {2008-05-16 08:38:26}, priority = {0}, citeulike-article-id = {543360},
	keywords = {ir }
}

@book{vanRijsbergen1979,
	title = { Information retrieval },
	address = { London },
	author = {C. J. van Rijsbergen},
	edition = { 2 },
	publisher = { Butterworths },
	url = { http://www.dcs.glasgow.ac.uk/Keith/Preface.html },
	year = { 1979 },
	biburl = {http://www.bibsonomy.org/bibtex/293daeee8205d4f98b6880f7935c69614/mgrani},
	abstract = { C. J. van Rijsbergen versucht in seinem
  Grundlagenwerk eine einfache und allgemeine Einf� in das Thema Information
  Retrieval zu geben. Es richtet sich an Studenten gleicherma�n wie an
  Wissenschafter im Feld der IR. Der Autor beschreibt Themen wie Automatische
  Text Analyse, Klassifikaion, Suchstrategien, Feedback und Bewertung der
  Effektivit� },
	keywords = {imported }
}