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This research proposes a method for capturing “relatedness between geographical entities” based on the co‐occurrences of their names on web pages. The basic assumption is that a higher count of co‐occurrences of two geographical places implies a stronger relatedness between them. The spatial structure of C hina at the provincial level is explored from the co‐occurrences of two provincial units in one document, extracted by a web information retrieval engine. Analysis on the co‐occurrences and topological distances between all pairs of provinces indicates that: (1) spatially close provinces generally have similar co‐occurrence patterns; (2) the frequency of co‐occurrences exhibits a power law distance decay effect with the exponent of 0.2; and (3) the co‐occurrence matrix can be used to capture the similarity/linkage between neighboring provinces and fed into a regionalization method to examine the spatial organization of C hina. The proposed method provides a promising approach to extracting valuable geographical information from massive web pages.
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Liu et al. (2013) studied this question.
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