@inproceedings{pub5665,
    series = {Lecture Notes in Computer Science, LNCS},
    abstract = {Since the availability of large digital image collections the need for a proper management of them raises. New technologies as annotations or tagging support the user by doing this task. However, this task is time-consuming and, therefore, automatic annotation systems are requested. Working outside of controlled laboratory environments this request is challenging. In this paper we propose a system automatically adapted to the user’s needs, providing useful annotations. We utilize Wikipedia to learn instances and abstract classes. With an evaluation in a complex use-case and dataset we show the possibility of such an attempt and achieve practical recognition rates of 26% on specific instance and 64% on abstract class level.},
    month = {9},
    year = {2011},
    title = {Semantic Retrieval of Images by Learning from Wikipedia},
    booktitle = {Knowledge-Based and Intelligent Information and Engineering Systems. International Conference on Knowledge-Based and Intelligent Information & Engineering Systems (KES-2011), September 12-14, Kaiserslautern, Germany},
    editor = {Andreas König and Andreas Dengel and Knut Hinkelmann and Koichi Kise and Robert J. Howlett and Lakhmi C. Jain},
    volume = {6884},
    pages = {212-221},
    isbn = {978-3-642-23865-9},
    publisher = {Springer},
    author = {Martin Klinkigt and Koichi Kise and Heiko Maus and Andreas Dengel},
    keywords = {SIFT, shape model, SVM, image management, specific object recognition, generic object recognition},
    organization = {KES},
    url = {http://dx.doi.org/10.1007/978-3-642-23866-6_23}
}