@inproceedings{haase2005usagedriven,
  abstract = {Large information repositories as digital libraries, online shops, etc. rely on a taxonomy of the objects under consideration to structure the vast contents and facilitate browsing and searching (e.g., ACM topic classification for computer science literature, Amazon product taxonomy, etc.). As in heterogeneous communities users typically will use different parts of such an ontology with varying intensity, customization and personalization of the ontologies is desirable. In this paper we adapt a collaborative filtering recommender system to assist users in the management and evolution of their personal ontology by providing detailed suggestions of ontology changes. Such a system has been implemented in the context of Bibster, a peer-to-peer based personal bibliography management tool. Finally, we report on an in-situ experiment with the Bibster community that shows the performance improvements over non-personalized recommendations.},
  address = {Las Vegas, Nevada USA},
  author = {Haase, Peter and Hotho, Andreas and Schmidt-Thieme, Lars and Sure, York},
  booktitle = {Proceedings of the 3rd International Conference on Universal A ccess in Human-Computer Interaction (UAHCI)},
  file = {haase2005usagedriven.pdf:haase2005usagedriven.pdf:PDF},
  groups = {public},
  interhash = {e5681c379cdfe126e44d034dac3fddad},
  intrahash = {05b1daa45aedb5c1f63683f961f17a9e},
  lastdatemodified = {2006-07-06},
  lastname = {Haase},
  month = {22-27 July},
  own = {notown},
  pdf = {Haase05.pdf},
  read = {notread},
  timestamp = {2007-05-25 16:05:53},
  title = {Usage-driven Evolution of Personal Ontologies},
  username = {dbenz},
  year = 2005
}

@inproceedings{haase2005collaborative,
  abstract = {Large information repositories as digital libraries, online shops, etc. rely on a taxonomy of the objects under consideration to structure the vast contents and facilitate browsing and searching (e.g., ACM topic classification for computer science literature, Amazon product taxonomy, etc.). As in heterogenous communities users typically will use different parts of such an ontology with varying intensity, customization and personalization of the ontologies is desirable. Of particular interest for supporting users during the personalization are collaborative filtering systems which can produce personal recommendations by computing the similarity between own preferences and the one of other people. In this paper we adapt a collaborative filtering recommender system to assist users in the management and evolution of their personal ontology by providing detailed suggestions of ontology changes. Such a system has been implemented in the context of Bibster, a peer-to-peer based personal bibliography management tool. Finally, we report on an experiment with the Bibster community that shows the performance improvements over non-personalized recommendations.},
  author = {Haase, Peter and Hotho, Andreas and Schmidt-Thieme, Lars and Sure, York},
  booktitle = {ESWC},
  crossref = {conf/esws/2005},
  date = {2005-05-24},
  editor = {Gómez-Pérez, Asunción and Euzenat, Jérôme},
  ee = {http://dx.doi.org/10.1007/11431053_33},
  file = {haase2005collaborative.pdf:haase2005collaborative.pdf:PDF},
  groups = {public},
  interhash = {c9ba81293a1b27f1c9bdf38a3beec060},
  intrahash = {1a8829cde1cb26241a48901e28a953d2},
  isbn = {3-540-26124-9},
  pages = {486-499},
  publisher = {Springer},
  series = {Lecture Notes in Computer Science},
  timestamp = {2009-11-10 11:30:42},
  title = {Collaborative and Usage-Driven Evolution of Personal Ontologies.},
  url = {http://www.aifb.uni-karlsruhe.de/WBS/pha/publications/collaborative05eswc.pdf},
  username = {dbenz},
  volume = 3532,
  year = 2005
}

@inproceedings{marinho2008folksonomybased,
  abstract = {The growing popularity of social tagging systems promises to alleviate the knowledge bottleneck that slows down the full materialization of the SemanticWeb since these systems allow ordinary users to create and share knowledge in a simple, cheap, and scalable representation, usually known as folksonomy. However, for the sake of knowledge workflow, one needs to find a compromise between the uncontrolled nature of folksonomies and the controlled and more systematic vocabulary of domain experts. In this paper we propose to address this concern by devising a method that automatically enriches a folksonomy with domain expert knowledge and by introducing a novel algorithm based on frequent itemset mining techniques to efficiently learn an ontology over the enriched folksonomy. In order to quantitatively assess our method, we propose a new benchmark for task-based ontology evaluation where the quality of the ontologies is measured based on how helpful they are for the task of personalized information finding. We conduct experiments on real data and empirically show the effectiveness of our approach.},
  author = {Marinho, Leandro Balby and Buza, Krisztian and Schmidt-Thieme, Lars},
  booktitle = {International Semantic Web Conference},
  crossref = {conf/semweb/2008},
  date = {2008-10-24},
  editor = {Sheth, Amit P. and Staab, Steffen and Dean, Mike and Paolucci, Massimo and Maynard, Diana and Finin, Timothy W. and Thirunarayan, Krishnaprasad},
  ee = {http://dx.doi.org/10.1007/978-3-540-88564-1_17},
  file = {marinho2008folksonomybased.pdf:marinho2008folksonomybased.pdf:PDF},
  groups = {public},
  interhash = {d295e7d4615500c670e70ad240fada29},
  intrahash = {cfa4c4520d4cf02e03dd3b84bb5c9578},
  isbn = {978-3-540-88563-4},
  pages = {261-276},
  publisher = {Springer},
  series = {Lecture Notes in Computer Science},
  timestamp = {2010-03-30 16:14:58},
  title = {Folksonomy-Based Collabulary Learning.},
  url = {http://dblp.uni-trier.de/db/conf/semweb/iswc2008.html#MarinhoBS08},
  username = {dbenz},
  volume = 5318,
  year = 2008
}