Abstract
Many discovery methods for geographic information services have been proposed. There are approaches for finding and matching geographic information services, methods for constructing geographic information service classification schemes, and automatic geographic information discovery. Overall, the efficiency of the geographic information discovery keeps improving., There are however, still two problems in Web Map Service (WMS) discovery that must be solved. Mismatches between the graphic contents of a WMS and the semantic descriptions in the metadata make discovery difficult for human users. End-users and computers comprehend WMSs differently creating semantic gaps in human-computer interactions. To address these problems, we propose an improved query process for WMSs based on the graphic contents of WMS layers, combining Support Vector Machine (SVM) and user relevance feedback. Our experiments demonstrate that the proposed method can improve the accuracy and efficiency of WMS discovery.
Highlights
The number of online GIServices has increased dramatically in recent years with the development of geospatial sharing technologies and the emergence of many open government data initiatives
We used a Web Map Service (WMS) layer dataset collected in advance as test dataset, a total of 653 WMSs with 11689 available layers
Our experiments demonstrate that the proposed method can improve the accuracy of WMS search but the performance varies when dealing with different feature types
Summary
The number of online GIServices has increased dramatically in recent years with the development of geospatial sharing technologies and the emergence of many open government data initiatives. According to a recent global-scale resource survey of the Web Map Service (WMS) standard proposed by Open Geospatial Consortium (OGC), there are more than 40 thousand valid WMSs publicly available globally on diverse map subjects, geographic extents and projections [1]. The booming of online GIServices has enhanced geospatial research and applications, and has created new challenges for GIService discovery and selection. To improve discovery of desired geographic information services (GIServices) researchers have proposed different methods to improve web service metadata, data provenance, and PLOS ONE | DOI:10.1371/journal.pone.0166098. To improve discovery of desired geographic information services (GIServices) researchers have proposed different methods to improve web service metadata, data provenance, and PLOS ONE | DOI:10.1371/journal.pone.0166098 November 18, 2016
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