Abstract
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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Wang, X., Chen, D., Lu, G., Peng, Y., Hu, C. (2014). Web Map Service Log Analysis. In: Cai, Z., Wang, C., Cheng, S., Wang, H., Gao, H. (eds) Wireless Algorithms, Systems, and Applications. WASA 2014. Lecture Notes in Computer Science, vol 8491. Springer, Cham. https://doi.org/10.1007/978-3-319-07782-6_3
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DOI: https://doi.org/10.1007/978-3-319-07782-6_3
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