NicolaeO DiaconescuIM GiurcaA WagnerG NicolaeOana DiaconescuIon-Mircea GiurcaAdrian WagnerGerd NegruV JebeleanT PetcuD ZaharieD Sharing rules between JBoss and Jena NINTH INTERNATIONAL SYMPOSIUM ON SYMBOLIC AND NUMERIC ALGORITHMS FOR SCIENTIFIC COMPUTING, PROCEEDINGS 9th International Symposium on Symbolic and Numeric Algorithms for Scientific Computing W Univ Timisoara The actual rule based implementations point to different rule target platforms and languages (Object Oriented Rule Languages, Semantic Web Rule Languages, Artificial Intelligence Rule Languages) in a business landscape dominated by a limited number of tool vendors as well as competitive open-source platforms and rule interoperability initiatives. This work provides a description of business rules translation from JBoss-Rules - an Object Oriented rule-system, to JenaRules - a Semantic Web rule-system, via an interchange language. It focuses on the general lines of the JBoss-R2ML-Jena translation and to outline the limitations and on the correctness of the proposed interchange. 978-0-7695-3078-9 2007 105 108 000264583000015 HeRH XiongNX KimTH ZhuY HeRuhan XiongNaixue KimTai-hoon ZhuYong Mining Cross-Modal Association Rules for Web Image Retrieval CSA 2008: INTERNATIONAL SYMPOSIUM ON COMPUTER SCIENCE AND ITS APPLICATIONS, PROCEEDINGS International Symposium on Computer Science and Its Applications To alleviate the known semantic gap, it is necessary to integrate the two-modal parts of web images, i.e. the low-level visual features and high-level semantic concepts (which are usually represented by keywords), for web image retrieval. In this paper, we associate the keyword and visual features of web images from a different prospective and a new approach based on the cross-modal association rules is proposed to automatically integrate the keyword and visual features for web image retrieval. A customized mining process is developed for the special association rule that crosses the two modals of web images. The cross-modal association rule effectively associates the keyword and visual feature clusters, and seamlessly integrates the two modals of web images in retrieval process. The proposed approach is utilized successfully in a web image retrieval system named VAST VisuAl SemanTic image search. 978-0-7695-3428-2 2008 393 396 000264587200073 DongH HussainFK ChangE DongHai HussainFarookh Khadeer ChangElizabeth A Survey in Semantic Search Technologies IEEE 2008 2ND IEEE INTERNATIONAL CONFERENCE ON DIGITAL ECOSYSTEMS AND TECHNOLOGIES IEEE International Conference on Digital Ecosystems and Technologies 2nd IEEE International Conference on Digital Ecosystems and Technologies In this paper, we make a survey over the primary literature regarding semantic search technologies. By classifying the literature into six main categories, we review their characteristics respectively. In addition, the issues within the reviewed semantic search methods and engines are analysed and concluded based on four perspectives. 978-1-4244-1489-5 2008 422 427 000264749700067