A Quantitative Similarity Measure for Maps

作者: Richard Frank , Martin Ester

DOI: 10.1007/3-540-35589-8_28

关键词:

摘要: In on-demand map generation, a base-map is modified to meet user requirements on scale, resolution, and other parameters. Since there are many ways of satisfying the requirement, we need method measuring quality alternative maps. this paper, introduce uniform framework for generalized The proposed Map Quality measure takes into account changes in all local objects (Shape Similarity), their neighborhoods (Location Similarity) lastly across entire (Semantic Content Similarity). These three aspects major generalization operators simplification, relocation selection, exaggeration aggregation, collapse typification. different combined using user-specified weights. Thus, supports automatic choice best according preferences or application.

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