Computing Geographical Scopes of Web Resources
VLDB '00 Proceedings of the 26th International Conference on Very Large Data Bases
Spatial variation in search engine queries
Proceedings of the 17th international conference on World Wide Web
Towards Click-Based Models of Geographic Interests in Web Search
WI-IAT '08 Proceedings of the 2008 IEEE/WIC/ACM International Conference on Web Intelligence and Intelligent Agent Technology - Volume 01
Computing geographical serving area based on search logs and website categorization
DEXA'07 Proceedings of the 18th international conference on Database and Expert Systems Applications
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Local search engines allow users to search for entities such as businesses in a particular geographic location. To improve the geographic relevance of search, user feedback data such as logged click locations are traditionally used. In this paper, we use anonymized mobile call log data as an alternate source of data and investigate its relevance to local search. Such data consists of records of anonymized mobile calls made to local businesses along with the locations of celltowers that handled the calls. We model the probability of calls made to particular categories of businesses as a function of distance, using a generalized linear model framework. We provide a detailed comparison between a click log and a mobile call log, showing its relevance to local search. We describe our probabilistic models and apply them to anonymized mobile call logs for New York City and Los Angeles restaurants.