Context as a factor in personal information management systems
Journal of the American Society for Information Science
User interactions with everyday applications as context for just-in-time information access
Proceedings of the 5th international conference on Intelligent user interfaces
Mining navigation history for recommendation
Proceedings of the 5th international conference on Intelligent user interfaces
Extracting usability information from user interface events
ACM Computing Surveys (CSUR)
Modern Information Retrieval
Using Document Access Sequences to Recommend Customized Information
IEEE Intelligent Systems
UMEA: translating interaction histories into project contexts
Proceedings of the SIGCHI Conference on Human Factors in Computing Systems
Stuff I've seen: a system for personal information retrieval and re-use
Proceedings of the 26th annual international ACM SIGIR conference on Research and development in informaion retrieval
Adaptive web search based on user profile constructed without any effort from users
Proceedings of the 13th international conference on World Wide Web
Personalizing search via automated analysis of interests and activities
Proceedings of the 28th annual international ACM SIGIR conference on Research and development in information retrieval
Connections: using context to enhance file search
Proceedings of the twentieth ACM symposium on Operating systems principles
Searching to eliminate personal information management
Communications of the ACM - Personal information management
Evaluating personal information management behaviors and tools
Communications of the ACM - Personal information management
A hybrid learning system for recognizing user tasks from desktop activities and email messages
Proceedings of the 11th international conference on Intelligent user interfaces
SWISH: semantic analysis of window titles and switching history
Proceedings of the 11th international conference on Intelligent user interfaces
A study on the effects of personalization and task information on implicit feedback performance
CIKM '06 Proceedings of the 15th ACM international conference on Information and knowledge management
What do people recall about their documents?: implications for desktop search tools
Proceedings of the 12th international conference on Intelligent user interfaces
CAAD: an automatic task support system
Proceedings of the SIGCHI Conference on Human Factors in Computing Systems
Personalized query expansion for the web
SIGIR '07 Proceedings of the 30th annual international ACM SIGIR conference on Research and development in information retrieval
Towards task-based personal information management evaluations
SIGIR '07 Proceedings of the 30th annual international ACM SIGIR conference on Research and development in information retrieval
Confluence: enhancing contextual desktop search
SIGIR '07 Proceedings of the 30th annual international ACM SIGIR conference on Research and development in information retrieval
Proceedings of the 14th international conference on Intelligent user interfaces
The case for browser provenance
TAPP'09 First workshop on on Theory and practice of provenance
Segment-level display time as implicit feedback: a comparison to eye tracking
Proceedings of the 32nd international ACM SIGIR conference on Research and development in information retrieval
Which version is this?: improving the desktop experience within a copy-aware computing ecosystem
Proceedings of the SIGCHI Conference on Human Factors in Computing Systems
Proceedings of the 21st international conference on World Wide Web
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As the user's document and application workspace grows more diverse, supporting personal information management becomes increasingly important. This trend toward diversity renders it difficult to implement systems which are tailored to specific applications, file types, or other information sources. We developed SeeTrieve, a personal document retrieval and classification system which abstracts applications by considering only the text they present to the user through the user interface. Associating the visible text which surrounds a document in time, SeeTrieve is able to identify important information about the task within which a document is used. This context enables novel, useful ways for users to retrieve their personal documents. When compared to content based systems, this context based retrieval achieved substantial improvements in document recall.