Space/time trade-offs in hash coding with allowable errors
Communications of the ACM
Impedance coupling in content-targeted advertising
Proceedings of the 28th annual international ACM SIGIR conference on Research and development in information retrieval
Finding advertising keywords on web pages
Proceedings of the 15th international conference on World Wide Web
A semantic approach to contextual advertising
SIGIR '07 Proceedings of the 30th annual international ACM SIGIR conference on Research and development in information retrieval
Effects of intelligent notification management on users and their tasks
Proceedings of the SIGCHI Conference on Human Factors in Computing Systems
Keyword extraction for contextual advertisement
Proceedings of the 17th international conference on World Wide Web
How much can behavioral targeting help online advertising?
Proceedings of the 18th international conference on World wide web
A contextual-bandit approach to personalized news article recommendation
Proceedings of the 19th international conference on World wide web
Proceedings of the 8th international conference on Mobile systems, applications, and services
TaintDroid: an information-flow tracking system for realtime privacy monitoring on smartphones
OSDI'10 Proceedings of the 9th USENIX conference on Operating systems design and implementation
Proceedings of the 20th international conference companion on World wide web
Microsoft XNA Framework Edition: Programming Windows Phone 7
Microsoft XNA Framework Edition: Programming Windows Phone 7
Web Page Summarization for Just-in-Time Contextual Advertising
ACM Transactions on Intelligent Systems and Technology (TIST)
Where is the energy spent inside my app?: fine grained energy accounting on smartphones with Eprof
Proceedings of the 7th ACM european conference on Computer Systems
AdNext: a visit-pattern-aware mobile advertising system for urban commercial complexes
Proceedings of the 12th Workshop on Mobile Computing Systems and Applications
Unsafe exposure analysis of mobile in-app advertisements
Proceedings of the fifth ACM conference on Security and Privacy in Wireless and Mobile Networks
Empowering developers to estimate app energy consumption
Proceedings of the 18th annual international conference on Mobile computing and networking
Privacy-aware personalization for mobile advertising
Proceedings of the 2012 ACM conference on Computer and communications security
AppInsight: mobile app performance monitoring in the wild
OSDI'12 Proceedings of the 10th USENIX conference on Operating Systems Design and Implementation
CAMEO: a middleware for mobile advertisement delivery
Proceeding of the 11th annual international conference on Mobile systems, applications, and services
Prefetching mobile ads: can advertising systems afford it?
Proceedings of the 8th ACM European Conference on Computer Systems
Proceedings of the Twenty-Fourth ACM Symposium on Operating Systems Principles
ACM SIGOPS 24th Symposium on Operating Systems Principles
Timecard: controlling user-perceived delays in server-based mobile applications
Proceedings of the Twenty-Fourth ACM Symposium on Operating Systems Principles
DECAF: detecting and characterizing ad fraud in mobile apps
NSDI'14 Proceedings of the 11th USENIX Conference on Networked Systems Design and Implementation
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A recent study showed that while US consumers spent 30% more time on mobile apps than on traditional web, advertisers spent 1600% less money on mobile ads. One key reason is that unlike most web ad providers, today's mobile ads are not contextual---they do not take into account the content of the page they are displayed on. Thus, most mobile ads are irrelevant to what the user is interested in. For example, it is not uncommon to see gambling ads being displayed in a Bible app. This irrelevance results in low clickthrough rates, and hence advertisers shy away from the mobile platform. Using data from top 1200 apps in Windows Phone marketplace, and a one-week trace of ad keywords from Microsoft's ad network, we show that content displayed by mobile apps is a potential goldmine of keywords that advertisers are interested in. However, unlike web pages, which can be crawled and indexed offline for contextual advertising, content shown on mobile apps is often either generated dynamically, or is embedded in the apps themselves; and hence cannot be crawled. The only solution is to scrape the content at runtime, extract keywords and fetch contextually relevant ads. The challenge is to do this without excessive overhead and without violating user privacy. In this paper, we describe a system called SmartAds to address this challenge. We have built a prototype of SmartAds for Windows Phone apps. In a large user study with over 5000 ad impressions, we found that SmartAds nearly doubles the relevance score, while consuming minimal additional resources and preserving user privacy.