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MOBICOM
2010
ACM
15 years 4 months ago
Profiling users in a 3g network using hourglass co-clustering
With widespread popularity of smart phones, more and more users are accessing the Internet on the go. Understanding mobile user browsing behavior is of great significance for seve...
Ram Keralapura, Antonio Nucci, Zhi-Li Zhang, Lixin...
KDD
2009
ACM
232views Data Mining» more  KDD 2009»
15 years 9 months ago
Probabilistic latent semantic user segmentation for behavioral targeted advertising
Behavioral Targeting (BT), which aims to deliver the most appropriate advertisements to the most appropriate users, is attracting much attention in online advertising market. A ke...
Xiaohui Wu, Jun Yan, Ning Liu, Shuicheng Yan, Ying...
ECRIME
2007
15 years 8 months ago
Getting users to pay attention to anti-phishing education: evaluation of retention and transfer
Educational materials designed to teach users not to fall for phishing attacks are widely available but are often ignored by users. In this paper, we extend an embedded training m...
Ponnurangam Kumaraguru, Yong Rhee, Steve Sheng, Sh...
HT
2010
ACM
15 years 6 months ago
Capturing implicit user influence in online social sharing
Online social sharing sites are becoming very popular nowadays among Web users, who use these sites to share their favourite items and to discover interesting and useful items fro...
Ching-man Au Yeung, Tomoharu Iwata
WWW
2009
ACM
16 years 5 months ago
Computers and iphones and mobile phones, oh my!: a logs-based comparison of search users on different devices
We present a logs-based comparison of search patterns across three platforms: computers, iPhones and conventional mobile phones. Our goal is to understand how mobile search users ...
Maryam Kamvar, Melanie Kellar, Rajan Patel, Ya Xu