@article{voelker2008aeon,
  abstract = {OntoClean is an approach towards the formal evaluation of taxonomic relations in ontologies. The application of OntoClean consists of two main steps. First, concepts are tagged according to meta-properties known as rigidity, unity, dependency and identity. Second, the tagged concepts are checked according to predefined constraints to discover taxonomic errors. Although OntoClean is well documented in numerous publications, it is still used rather infrequently due to the high costs of application. Especially, the manual tagging of concepts with the correct meta-properties requires substantial efforts of highly experienced ontology engineers. In order to facilitate the use of OntoClean and to enable the evaluation of real-world ontologies, we provide AEON, a tool which automatically tags concepts with appropriate OntoClean meta-properties and performs the constraint checking. We use the Web as an embodiment of world knowledge, where we search for patterns that indicate how to properly tag concepts. We thoroughly evaluated our approach against a manually created gold standard. The evaluation shows the competitiveness of our approach while at the same time significantly lowering the costs. All of our results, i.e. the tool AEON as well as the experiment data, are publicly available.},
  address = {Amsterdam, The Netherlands, The Netherlands},
  author = {Völker, Johanna and Vrandečić, Denny and Sure, York and Hotho, Andreas},
  interhash = {f14794f4961d0127dc50c1938eaef7ea},
  intrahash = {f8f0bb3e3495e7627770b470d1a5f1a3},
  issn = {1570-5838},
  journal = {Applied Ontology},
  number = {1-2},
  pages = {41--62},
  publisher = {IOS Press},
  title = {AEON - An approach to the automatic evaluation of ontologies},
  url = {http://portal.acm.org/citation.cfm?id=1412422},
  volume = 3,
  year = 2008
}

@article{4563045,
  abstract = {Image annotation is hard to do in an automatic way. In this paper, we propose a framework for image annotation that combines the benefits of three paradigms: automatic annotation, human intervention and entertainment activities. We also describe our proposal inside this framework, the ASAA (application for semi-automatic annotation) interface, a new computer game for image tagging. The application has a 3D game interface, and is supported by a game engine that uses a system for automatic image classification and gestural input to play the game. We present results of the performance of semantic models obtained with a training set enlarged by images annotated during the game activity as well as usability tests of the application.},
  author = {Jesus, R. and Goncalves, D. and Abrantes, A.J. and Correia, N.},
  doi = {10.1109/CVPRW.2008.4563045},
  interhash = {cdd13517badd0fdd5d6455a6ea971cb4},
  intrahash = {0190ab8d7a4603a19c795e205fdf87ca},
  journal = {Computer Vision and Pattern Recognition Workshops, 2008. CVPR Workshops 2008. IEEE Computer Society Conference on},
  month = {June},
  pages = {1-8},
  title = {Playing games as a way to improve automatic image annotation},
  year = 2008
}