Shengsheng Wang

A survey of qualitative spatial representations

Representation and reasoning with qualitative spatial relations is an important problem in artificial intelligence and has wide applications in the fields of geographic information system, computer vision, autonomous robot navigation, natural language understanding, spatial databases and so on. The reasons for this interest in using qualitative spatial relations include cognitive comprehensibility, efficiency and computational facility. This paper summarizes progress in qualitative spatial representation by describing key calculi representing different types of spatial relationships. The paper concludes with a discussion of current research and glimpse of future work.

Spatial Description Logic and Its Application in Geospatial Semantic Web

Classical description logics deal with the concept and instance reasoning, while qualitative spatial reasoning handles the geospatial relations of objects. In geospatial semantic web, cooperation of these two kinds of reasoning tasks is required. Thatpsilas the motive of our spatial description logic. A general spatial representation and reasoning method with ALC is proposed. The constraints satisfaction problem for spatial relation can be solved within ExpTime-complete time, while the previous spatial description logics are all undecidable. Integrating of multi-aspects spatial relation models is also discussed. Finally, a prototype system is given to show its application in geospatial semantic web.

A Feature Selection Method Based on Multi-objective Optimisation with Gravitational Search Algorithm

The process of feature selection (FS) is a substantial task that has a significant effect in the performance of a given algorithm. The goal is to choose a subset of available features by eliminating the unnecessary features. This hybrid algorithm is in maximising the classification performance and minimising the number of features to achieve an outstanding performance through a less complex procedure. From the experiments, FSMOGSA was noted to be quite unparalleled in comparison with other methods in reducing the error rate, and maximising the general performance through irrelevant feature reduction.

Multi-granularities approximate method for obtaining qualitative spatial relations

Qualitative spatial relations are widely used in spatial description logics, spatial ontologies and other applications. Efficient method to obtain qualitative spatial relations from traditional GIS has not been discussed in previous literatures. We give an efficient method for calculating qualitative spatial relations. We propose the multi-granularities approximate representation of GIS objects which requires less process time. Then some algorithms are proposed to calculate the spatial relations based on multi-granularities approximate region. The analysis and test result all show that our method supports complex and integrated spatial relations and require less process time than traditional spatial query.

Qualitative Spatio-Temporal Database

The traditional spatio-temporal database stores the quantitative data such as coordinate. But the qualitative information is more close to human thought and requires less storage space and process time. The previous qualitative spatio-temporal systems were all prototype systems which did not support general spatio-temporal relation model and data input. We design the qualitative spatio-temporal database (QSTDB) based on spatio-temporal reasoning. A general spatio-temporal relation framework is put forward and applied to QSTDB. GML data can be converted to QSTDB as input. Thus QSTDB is compatible to most current spatio-temporal relation models and spatio-temporal systems. QSTDB can be applied to qualitative spatio-temporal query, spatio-temporal ontologies, spatio-temporal data mining and way finding systems etc

Asynchronous Updating Algorithm for Continuous Moving Objects Queries

Continuous queries for moving objects are becoming more and more important due to the increasing number of application domains that deal with moving entities. The asynchronous updating algorithm for continuous queries of moving objects is superior to synchronous updating algorithms in communication cost. By improving Haibo Hus rectangle safe region strategy we proposed a new continuous queries algorithm. Circle safe region and dynamic interval are adopted in our algorithm. Theory proof and experiment results show that our algorithm substantially outperforms the traditional periodic monitoring and the rectangle safe region algorithms in terms of monitoring accuracy, communication cost and CPU time. Furthermore, the mobile terminals need not have any computation ability in our algorithm

Improved Algorithm For Continuous Moving Objects Queries

Moving objects databases are becoming more and more popular due to the increasing number of application domains that deal with moving entities. Continuous queries are important in moving objects databases. We summarize three types of continuous queries, but only two of them have been studied before. We proposed new algorithms to process the other two types of queries. Experiment results all show that our algorithm is excellent in monitoring accuracy, communication cost and CPU load balance