Barrat S Tabbone S Barrat Sabine Tabbone Salvatore IEEE Visual Features with Semantic Combination Using Bayesian Network for a More Effective Image Retrieval 19TH INTERNATIONAL CONFERENCE ON PATTERN RECOGNITION, VOLS 1-6 INTERNATIONAL CONFERENCE ON PATTERN RECOGNITION 19th International Conference on Pattern Recognition (ICPR 2008) In many vision problems, instead of having fully annotated training data, it is easier to obtain just a subset of data with annotations, because it is less restrictive for the user. For this reason, in this paper, we consider especially the problem of weakly-annotated image retrieval, where just a small subset of the database is annotated with keywords. We present and evaluate a new method which improves the effectiveness of content-based image retrieval, by integrating semantic concepts extracted from text. Our model is inspired from the probabilistic graphical model theory: we propose a hierarchical mixture model which enables to handle missing values and to capture the users preference by also considering a relevance feedback process. Results of visual-textual retrieval associated to a relevance feedback process, reported on a database of images collected from the Web, partially and manually annotated, show an improvement of about 44.5% in terms of recognition rate against content-based retrieval. 1051-4651 978-1-4244-2174-9 000264729000219 Liu WY Hao TY Chen W Feng M Liu Wenyin Hao Tianyong Chen Wei Feng Min A Web-Based Platform for User-Interactive Question-Answering WORLD WIDE WEB-INTERNET AND WEB INFORMATION SYSTEMS A user-interactive question-answering (QA) platform named BuyAns (at www.buyans.com) is presented. The platform is a special kind of online community and mainly features a rewarding scheme for answering questions among all users, a pattern-based user interface (UI) for questioning and answering, and a pattern-based representation and storage scheme for accumulated question-answer pairs. The system actually proposes and promotes a C2C business model for exchanging and commercializing knowledge from ordinary people. It can also be used as an incentive and collaborative approach to knowledge acquisition. Driven by the business model, prompt and quality answers are quickly accumulated. Due to the patterns used, accurate answers can be provided automatically for repeated questions. Facilitating features and technologies, including user modeling, reputation management, and answer clustering and fusion, are also developed and briefly described. Preliminary user studies show the potential attraction of the system to its users as well as reasonable usability and user-satisfaction. We anticipate hot applications of such a system in the Web 2.0 era. 1386-145X 2 10.1007/s11280-008-0051-3 000264621800001 Huang RC Zhuang YW Zhou JL Cao QY Huang Runcai Zhuang Yiwen Zhou Jiliang Cao Qiying Zhu J Semantic Web-Based Context-Aware Service Selection in Task-Computing WMSO: 2008 INTERNATIONAL WORKSHOP ON MODELLING, SIMULATION AND OPTIMIZATION, PROCEEDINGS International Workshop on Modelling, Simulation and Optimization The hierarchy of task-computing and the decomposition strategy of complex task are analyzed according to the characteristics of task-computing in pervasive environment. The architecture relies on the semantic representation of service and content, however, the semantic representation is based on shared ontology. It can not only improve the accuracy and recall, but also realize the functions such as knowledge sharing, capability-based search, autonomous reasoning and semantic matchmaking. Thus, a dynamic semantic Web-based context aware service selection mechanism is proposed to filter and rank the matching services according to their dynamic context in order to optimize the discovery process and save the time and effort of users. In addition, the selection mechanism can be used to discover the useful static and dynamic context information to provide the most suitable and relative services for users. 978-0-7695-3484-8 000264431400022 Mencke S Wille C Dumke R Mencke Steffen Wille Cornelius Dumke Reiner Dumke RR Braungarten R Buren G Abran A CuadradoGallego JJ Measuring Distances for Ontology-Based Systems SOFTWARE PROCESS AND PRODUCT MEASUREMENT LECTURE NOTES IN COMPUTER SCIENCE Joint Meeting of the International Workshop on Software Measurement (IWSM)/MetriKon/Mensura 2008 Nowadays, measurement and assessment of artifacts within the area of software development are of high concern for scientific institutions. With the increasing usage of the Web 2.0, together with service-oriented applications, the importance of Web-based systems is still growing. Ontologies as a fundamental concept of the Semantic Web as envisioned by Tim Berners-Lee, play an important role for current and future applications. To promote the high flexibility of this technology for international dynamics, additional concepts for the Semantic Web are necessary. Ontology metrics are used to measure certain aspects of ontologies. In this paper, a set of novel distance metrics is introduced and their applicability is proven by the presentation of an example. 0302-9743 978-3-540-89402-5 000264341700009