title: Content-Based Discovery for Web Map Service using Support Vector Machine and User Relevance Feedback.
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.
authors.affiliation: State Key Laboratory of Information Engineering in Surveying, Mapping and Remote Sensing, Wuhan University, Wuhan, China.|Collaborative Innovation Center of Geospatial Technology, Wuhan University, Wuhan, China.
authors.forename: Kai
authors.identifier: http://orcid.org/0000-0002-3521-4178
authors.initials: K
authors.lastname: Hu
authors.affiliation: School of Remote Sensing and Information Engineering, Wuhan University, Wuhan, China.|Collaborative Innovation Center of Geospatial Technology, Wuhan University, Wuhan, China.
authors.forename: Zhipeng
authors.identifier: http://orcid.org/0000-0001-9467-9680
authors.initials: Z
authors.lastname: Gui
authors.affiliation: Faculty of Resources and Environmental Science, Hubei University, Wuhan, China.
authors.forename: Xiaoqiang
authors.initials: X
authors.lastname: Cheng
authors.affiliation: National Engineering Research Center for Geographic Information System, China, University of Geosciences, Wuhan, China.
authors.forename: Kunlun
authors.initials: K
authors.lastname: Qi
authors.affiliation: State Key Laboratory of Information Engineering in Surveying, Mapping and Remote Sensing, Wuhan University, Wuhan, China.
authors.forename: Jie
authors.initials: J
authors.lastname: Zheng
authors.affiliation: Faculty of Computer Science and Information Engineering, Hubei University, Wuhan, China.
authors.forename: Lan
authors.initials: L
authors.lastname: You
authors.affiliation: State Key Laboratory of Information Engineering in Surveying, Mapping and Remote Sensing, Wuhan University, Wuhan, China.|Collaborative Innovation Center of Geospatial Technology, Wuhan University, Wuhan, China.
authors.forename: Huayi
authors.initials: H
authors.lastname: Wu
mesh_terms: D000465:Algorithms; D005246:Feedback; D006801:Humans; D016247:Information Storage and Retrieval; D020407:Internet; D008377:Maps as Topic; D060388:Support Vector Machine; D014584:User-Computer Interface