Web Map Service Log Analysis

With the rapid growth of location-based services (LBS), web map service (WMS) is becoming indispensable in our daily life. From a new perspective, this paper measures and analyzes the user behaviors and regional differences in WMS, based on a big log dataset from the PC clients of a large-scale WMS provider. We give analysis on users' searching times from both macro and micro perspective, and point out that WMS data has a feature of searching behavior prediction, which is absent in other location-based datasets. Then, we observe and verify that the searching frequencies of point of interests in a city conform to Zipf distribution, and explain the underlying physical meanings of the corresponding parameters. In addition, we present a simple and intuitive approach to quantitatively study the inter-city fluidity and intra-city mobility patterns, and give semantic analysis on query categories in each city. And our work can serve as a measurement basis for future work in the area of WMS data mining.

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