Computational Statistics & Data Analysis - Nonlinear methods and data mining
A large scale study of wireless search behavior: Google mobile search
Proceedings of the SIGCHI Conference on Human Factors in Computing Systems
Mobile information access: A study of emerging search behavior on the mobile Internet
ACM Transactions on the Web (TWEB)
Determining the user intent of web search engine queries
Proceedings of the 16th international conference on World Wide Web
Learn from web search logs to organize search results
SIGIR '07 Proceedings of the 30th annual international ACM SIGIR conference on Research and development in information retrieval
Deciphering Trends in Mobile Search
Computer
Deciphering mobile search patterns: a study of Yahoo! mobile search queries
Proceedings of the 17th international conference on World Wide Web
A large scale study of European mobile search behaviour
Proceedings of the 10th international conference on Human computer interaction with mobile devices and services
Proceedings of the 18th international conference on World wide web
Fancy a Drink in Canary Wharf?: A User Study on Location-Based Mobile Search
INTERACT '09 Proceedings of the 12th IFIP TC 13 International Conference on Human-Computer Interaction: Part I
Model adaptation via model interpolation and boosting for web search ranking
EMNLP '09 Proceedings of the 2009 Conference on Empirical Methods in Natural Language Processing: Volume 2 - Volume 2
Proceedings of the Eleventh Workshop on Mobile Computing Systems & Applications
The demographics of web search
Proceedings of the 33rd international ACM SIGIR conference on Research and development in information retrieval
Personalize web search results with user's location
Proceedings of the 33rd international ACM SIGIR conference on Research and development in information retrieval
Proceedings of the 12th ACM international conference on Ubiquitous computing
Proceedings of the sixteenth international conference on Architectural support for programming languages and operating systems
UbiComp'06 Proceedings of the 8th international conference on Ubiquitous Computing
An exploration of ranking heuristics in mobile local search
SIGIR '12 Proceedings of the 35th international ACM SIGIR conference on Research and development in information retrieval
Web Semantics: Science, Services and Agents on the World Wide Web
On mining mobile apps usage behavior for predicting apps usage in smartphones
Proceedings of the 22nd ACM international conference on Conference on information & knowledge management
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Users increasingly rely on their mobile devices to search, locate and discover places and activities around them while on the go. Their decision process is driven by the information displayed on their devices and their current context (e.g. traffic, driving or walking etc.). Even though recent research efforts have already examined and demonstrated how different context parameters such as weather, time and personal preferences affect the way mobile users click on local businesses, little has been done to study how the location of the user affects the click behavior. In this paper we follow a data-driven methodology where we analyze approximately 2 million local search queries submitted by users across the US, to visualize and quantify how differently mobile users click across locations. Based on the data analysis, we propose new location-aware features for improving local search click prediction and quantify their performance on real user query traces. Motivated by the results, we implement and evaluate a data-driven technique where local search models at different levels of location granularity (e.g. city, state, and country levels) are combined together at run-time to further improve click prediction accuracy. By applying the location-aware features and the multiple models at different levels of location granularity on real user query streams from a major, commercially available search engine, we achieve anywhere from 5% to 47% higher Precision than a single click prediction model across the US can achieve.