Email overload: exploring personal information management of email
Proceedings of the SIGCHI Conference on Human Factors in Computing Systems
A design space approach to analysis of information retrieval adaptive filtering systems
Proceedings of the thirteenth ACM international conference on Information and knowledge management
Incorporating contextual information in recommender systems using a multidimensional approach
ACM Transactions on Information Systems (TOIS)
On the collective classification of email "speech acts"
Proceedings of the 28th annual international ACM SIGIR conference on Research and development in information retrieval
Automatically classifying emails into activities
Proceedings of the 11th international conference on Intelligent user interfaces
A simple approach to improving email communication
Communications of the ACM - Hacking and innovation
Probabilistic models for discovering e-communities
Proceedings of the 15th international conference on World Wide Web
Defining high-throughput email users
CHI '07 Extended Abstracts on Human Factors in Computing Systems
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This work is directed toward high-throughput email users, and uses machine learning and other artificial intelligence approaches to allow these users to triage and search email using automatically extracted social networks. While this approach makes use of (potentially) complex algorithms, these algorithms are abstracted through user interface design such that a non-technical user can take advantage of them, customizing when appropriate. My dissertation work will crystallize the needs of high-throughput email users into concrete tools to allow these users to better and more easily manage their information needs.