@inproceedings{hotho2006folkrank, title = {FolkRank: A Ranking Algorithm for Folksonomies}, author = {Andreas Hotho and Robert Jäschke and Christoph Schmitz and Gerd Stumme}, booktitle = {Proc. FGIR 2006}, pages = {to appear}, year = 2006, url = {http://www.kde.cs.uni-kassel.de/stumme/papers/2006/hotho2006folkrank.pdf}, description = {Short version of http://www.bibsonomy.org/bibtex/07f061a8c294bae64831fbe92dc9ece48/stumme}, abstract = { In social bookmark tools users are setting up lightweight conceptual structures called folksonomies. Currently, the information retrieval support is limited. We present a formal model and a new search algorithm for folksonomies, called FolkRank, that exploits the structure of the folksonomy. The proposed algorithm is also applied to find communities within the folksonomy and is used to structure search results. All findings are demonstrated on a large scale dataset. A long version of this paper has been published at the European Semantic Web Conference 2006.}, biburl = {http://www.bibsonomy.org/bibtex/24d8b4f79814691fbe6db8357d63206a1/grahl}, keywords = {informationretrieval nepomuk pagerank folkrank ranking algorithm} } @inproceedings{hotho2006information, title = {Information Retrieval in Folksonomies: Search and Ranking}, address = {Heidelberg}, author = {Andreas Hotho and Robert Jäschke and Christoph Schmitz and Gerd Stumme}, booktitle = {The Semantic Web: Research and Applications}, editor = {York Sure and John Domingue}, month = {June}, pages = {411-426}, publisher = {Springer}, series = {LNAI}, volume = 4011, year = 2006, url = {http://www.kde.cs.uni-kassel.de/stumme/papers/2006/hotho2006information.pdf}, abstract = {Social bookmark tools are rapidly emerging on the Web. In such systems users are setting up lightweight conceptual structures called folksonomies. The reason for their immediate success is the fact that no specific skills are needed for participating. At the moment, however, the information retrieval support is limited. We present a formal model and a new search algorithm for folksonomies, called \emph{FolkRank}, that exploits the structure of the folksonomy. The proposed algorithm is also applied to find communities within the folksonomy and is used to structure search results. All findings are demonstrated on a large scale dataset.}, biburl = {http://www.bibsonomy.org/bibtex/23c301945817681d637ee43901c016939/grahl}, keywords = {folkrank ranking pagerank information folksonomy retrieval nepomuk informationretrieval} } @inproceedings{citeulike:818427, title = {Topic-based Vector Space Model}, address = {Colorado Springs}, author = {J. Becker and D. Kuropka}, booktitle = {Proceedings of the 6th International Conference on Business Information Systems}, month = {July}, pages = {7--12}, year = 2003, url = {http://bpt.hpi.uni-potsdam.de/twiki/bin/view/Public/DominikKuropka}, id = {818427}, priority = {2}, description = {bibliografica tesi}, biburl = {http://www.bibsonomy.org/bibtex/2259513097151731f8ab2651c3338df35/grahl}, keywords = {vector-space-model informationretrieval} } @article{citeulike:818388, title = {Measuring retrieval effectiveness based on user preference of documents}, address = {Department of Mathematical Sciences, Lakehead University, Thunder Bay, Ontario P7B 5E1 Canada}, author = {Y. Y. Yao}, journal = {Journal of the American Society for Information Science}, number = 2, pages = {133--145}, volume = 46, year = 1995, url = {http://dx.doi.org/10.1002/(SICI)1097-4571(199503)46:2<133::AID-ASI6>3.0.CO;2-Z}, id = {818388}, priority = {2}, doi = {10.1002/(SICI)1097-4571(199503)46:2<133::AID-ASI6>3.0.CO;2-Z}, description = {bibliografica tesi}, abstract = {The notion of user preference is adopted for the representation, interpretation, and measurement of the relevance or usefulness of documents. User judgments on documents may be formally described by a weak order (i.e., user ranking) and measured using an ordinal scale. Within this framework, a new measure of system performance is suggested based on the distance between user ranking and system ranking. It only uses the relative order of documents and therefore confirms to the valid use of an ordinal scale measuring relevance. It is also applicable to multilevel relevance judgments and ranked system output. The appropriateness of the proposed measure is demonstrated through an axiomatic approach. The inherent relationships between the new measure and many existing measures provide further supporting evidence. © 1995 John Wiley \& Sons, Inc.}, biburl = {http://www.bibsonomy.org/bibtex/22259c92df0718ad8b85d1b02ac90d7aa/grahl}, keywords = {informationretrieval} } @inbook{baldi03modelling, title = {Modeling the Internet and the Web: Probabilistic Methods and Algorithms}, author = {Pierre Baldi and Paolo Frasconi and Padhraic Smyth}, booktitle = {Modeling the Internet and the Web: Probabilistic Methods and Algorithms}, chapter = 4, month = {April}, publisher = {Wiley}, year = 2003, url = {http://eu.wiley.com/WileyCDA/WileyTitle/productCd-0470849061.html}, id = {822915}, priority = {2}, description = {bibliografia tesi}, abstract = {Modeling the Internet and the Web covers the most important aspects of modeling the Web using a modern mathematical and probabilistic treatment. It focuses on the information and application layers, as well as some of the emerging properties of the Internet.  Provides a comprehensive introduction to the modeling of the Internet and the Web at the information level.  Takes a modern approach based on mathematical, probabilistic, and graphical modeling.  Provides an integrated presentation of theory, examples, exercises and applications.  Covers key topics such as text analysis, link analysis, crawling techniques, human behaviour, and commerce on the Web. Interdisciplinary in nature, Modeling the Internet and the Web will be of interest to students and researchers from a variety of disciplines including computer science, machine learning, engineering, statistics, economics, business, and the social sciences.}, biburl = {http://www.bibsonomy.org/bibtex/23e4e2899e7d6988218d02a264bcfe24a/grahl}, keywords = {informationretrieval data-mining tf-idf} } @article{salton75vector, title = {A vector space model for automatic indexing}, address = {New York, NY, USA}, author = {G. Salton and A. Wong and C. S. Yang}, journal = {Commun. ACM}, month = {November}, number = 11, pages = {613--620}, publisher = {ACM Press}, volume = 18, year = 1975, url = {http://dx.doi.org/10.1145/361219.361220}, description = {bibliografia tesi}, biburl = {http://www.bibsonomy.org/bibtex/2201304fb6db7593ccf8539fae8d316fe/grahl}, keywords = {informationretrieval tf-idf vector-space-model} } @misc{chakrabarti01managing, title = {Managing Large Multidimensional Datasets Inside A Database System}, author = {Kaushik Chakrabarti}, year = 2001, url = {http://citeseer.ist.psu.edu/chakrabarti01managing.html}, description = {Managing Large Multidimensional Datasets Inside A Database System (ResearchIndex)}, biburl = {http://www.bibsonomy.org/bibtex/24396233a3689ea75e3cf08080abda3ef/grahl}, keywords = {database informationretrieval} } @misc{barbara98quasicubes, title = {Quasi-cubes: A space-efficient way to support approximate multidimensional databases}, author = {D. Barbara}, year = 1998, url = {http://citeseer.ist.psu.edu/barbara98quasicubes.html}, biburl = {http://www.bibsonomy.org/bibtex/2dcab6910544097b0cd38f4621792b7d2/grahl}, keywords = {mathematics informationretrieval} } @book{rijsbergen79ir, title = {Information retrieval}, address = {London}, author = {C. J. van Rijsbergen}, edition = 2, publisher = {Butterworths}, year = 1979, url = {http://www.dcs.glasgow.ac.uk/Keith/Preface.html}, biburl = {http://www.bibsonomy.org/bibtex/2b53893655b48140d4310a848dbf204d3/grahl}, keywords = {AI informationretrieval} }