Categorizing web queries according to geographical locality
CIKM '03 Proceedings of the twelfth international conference on Information and knowledge management
Web-a-where: geotagging web content
Proceedings of the 27th annual international ACM SIGIR conference on Research and development in information retrieval
Web resource geographic location classification and detection
WWW '05 Special interest tracks and posters of the 14th international conference on World Wide Web
Detecting dominant locations from search queries
Proceedings of the 28th annual international ACM SIGIR conference on Research and development in information retrieval
Proceedings of the 4th ACM workshop on Geographical information retrieval
Discovering geographic locations in web pages using urban addresses
Proceedings of the 4th ACM workshop on Geographical information retrieval
Query expansion through geographical feature types
Proceedings of the 4th ACM workshop on Geographical information retrieval
Ontology-Based spatial query expansion in information retrieval
OTM'05 Proceedings of the 2005 OTM Confederated international conference on On the Move to Meaningful Internet Systems: CoopIS, COA, and ODBASE - Volume Part II
Geographic features in web search retrieval
Proceedings of the 2nd international workshop on Geographic information retrieval
Discovering users' specific geo intention in web search
Proceedings of the 18th international conference on World wide web
Placing flickr photos on a map
Proceedings of the 32nd international ACM SIGIR conference on Research and development in information retrieval
A case study of using geographic cues to predict query news intent
Proceedings of the 17th ACM SIGSPATIAL International Conference on Advances in Geographic Information Systems
Classifying Documents According to Locational Relevance
EPIA '09 Proceedings of the 14th Portuguese Conference on Artificial Intelligence: Progress in Artificial Intelligence
TWinner: understanding news queries with geo-content using Twitter
Proceedings of the 6th Workshop on Geographic Information Retrieval
Inferring and using location metadata to personalize web search
Proceedings of the 34th international ACM SIGIR conference on Research and development in Information Retrieval
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The number of search queries that are associated with geographical locations, either explicitly or implicitly, has been quadrupled in recent years. For such geo-sensitive queries, the ability to accurately infer users' geographical preference greatly enhances their search experience. By mining past user clicks and constructing a geographical click probability distribution model, we address two important issues in spatial Web search: how do we determine whether a search query is geo-sensitive, and how do we detect, disambiguate, and visualize the associated geographical location(s). We present our empirical study on a large-scale dataset with about 9,000 unique queries randomly drawn from the logs of a popular commercial search engine Yahoo! Search, and about 430 million user clicks on 1.6M unique Web pages over an eight-month period. Our classification method achieved recall of 0.98 and precision of 0.75 in identifying geo-sensitive search queries. We also present our preliminary findings in using geographical click probability distributions to cluster search results for queries with geographical ambiguities.