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.

A Latent Feature-Based Multimodality Fusion Method for Theme Classification on Web Map Service

“…Numerous visual features have been proposed to describe maps' visual appearance or infer their semantics, which achieved successful results. For example, [18] extracted distributed color histograms to measure users' preference on the map appearance. Particularly, to handle the semantic gap between visual features and themes, most studies tried to use the cartography standards or summarize some historical conventions on specific entities.…”

“…Reference [2] extracted keywords from metadata to conduct a topic survey on their crawled maps. Reference [18] matched users' queries with metadata to search for maps of users' interest. Furthermore, [22] used TFIDF to weight extracted words from metadata in classifying web services.…”

“…Some existing studies utilized the fusion of them to enhance their applications, and their results revealed significant improvement. For example, [18] used maps' similarity on appearance to refine metadata based search results. In addition, legends, as an interpreter for map symbols, tell what are included in the map, which could also provide complementary information for the theme classification.…”

The Concept and Technologies of Quality of Geographic Information Service: Improving User Experience of GIServices in a Distributed Computing Environment

“…These methods have been successfully used to design web UIs for better user experience [68]. More importantly, several attempts have been made to adjust to user experiences of GIService, such as map navigation [69], interactive online mapping designs [20], and feedback-based GIService retrieval [70]. However, the theory and application of usability testing in QoGIS research is still evolving since this interdisciplinary research links with many disciplines, such as cognition science and psychology.…”

“…According to the research, there are over 40 thousands WMSs deployed all over the world [62]. Thus, it is challengeable for end-users to find the best quality GIServices from such a large number of similar GIService candidates [70]. Most Spatial Data Infrastructure (SDI) and geoportals, such as GEOSS cleaning house, Data.gov, and INSPIRE, do not support quality-aware service discovery [71].…”