along with more and more trajectory dataset being collected into application servers, the research in trajectory clustering has become increasingly important topic. This paper proposes a new mobile object trajectory Clustering algorithm (Trajectory Clustering based Improved Minimum Hausdorff Distance under Translation, TraClustMHD). In this framework, improved Minimum Hausdorff Distance under Translation is presented to measure the similarity between sub-segments. In additional, R-Tree is employed to improve the efficiency. The experimental results showed that this algorithm better than based on Hausdorff distance and based on line Hausdorff distance has good trajectory clustering performance.

The Semantic Web envisions a World Wide Web in which datasources are encapsulated and described with rich semantics, and demander can issue complex queries. A critical problem in the situation is how to efficiently describe, organize and search these encapsulated datasources. This paper describes the Semantic Web-Based Data service(SWBDS for short) approach, which addresses these challenges. SWBDS introduces an ontology-based approach to, mapping web data sources to data service (DS for short), publishing DS with the shared domain ontology, and answering queries through DS provided interface. We define the domain ontology to illustrate the DS interface. The domain ontology is described in OWL that can be understood and processed by machines. Therefore, SWBDS can provide reasoning functions and facilitate datasources management with little human effort. This new system model makes full use of legacy applications and is flexible for future extensions.