Analyzing the browse patterns of mobile clients
IMW '01 Proceedings of the 1st ACM SIGCOMM Workshop on Internet Measurement
Characterizing Alert and Browse Services of Mobile Clients
ATEC '02 Proceedings of the General Track of the annual conference on USENIX Annual Technical Conference
SimRank: a measure of structural-context similarity
Proceedings of the eighth ACM SIGKDD international conference on Knowledge discovery and data mining
Scaling personalized web search
WWW '03 Proceedings of the 12th international conference on World Wide Web
Web-page classification through summarization
Proceedings of the 27th annual international ACM SIGIR conference on Research and development in information retrieval
Predicting navigation patterns on the mobile-internet using time of the week
WWW '05 Special interest tracks and posters of the 14th international conference on World Wide Web
Mobile web surfing is the same as web surfing
Communications of the ACM - Self managed systems
A large scale study of wireless search behavior: Google mobile search
Proceedings of the SIGCHI Conference on Human Factors in Computing Systems
Proceedings of the 18th international conference on World wide web
Adaptive web navigation for wireless devices
IJCAI'01 Proceedings of the 17th international joint conference on Artificial intelligence - Volume 2
A theoretical model for obfuscating web navigation trails
Proceedings of the Joint EDBT/ICDT 2013 Workshops
A survey on smartphone-based systems for opportunistic user context recognition
ACM Computing Surveys (CSUR)
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The World Wide Web has provided users with the opportunity to access from any computer the largest set of information ever existing Researchers have analyzed how such users surf the Web, and such analysis has been used to improve existing services (e.g., by means of data mining and personalization techniques) as well as the generation of new ones (e.g., online targeted advertisement) In recent years, a new trend has developed by which users do not need a computer to access the Web Instead, the low prices of mobile data connections allow them to access it anywhere anytime Some studies analyze how users access the Web on their handsets, but these studies use only navigation logs from a specific portal Therefore, very little attention (due to the complexity of obtaining the data) has been given to how users surf the Web (off-portal) from their mobiles and how that information could be used to build user profiles This paper analyzes full navigation logs of a large set of mobile users in a developed country, providing useful information about the way those users access the Web Additionally, it explores how navigation logs can be categorized, and thus user's interest can be modeled, by using online sources of information such as Web directories and social tagging systems.