Understanding and Using Context
Personal and Ubiquitous Computing
Towards a Better Understanding of Context and Context-Awareness
HUC '99 Proceedings of the 1st international symposium on Handheld and Ubiquitous Computing
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
Just-in-time information retrieval
Just-in-time information retrieval
What we talk about when we talk about context
Personal and Ubiquitous Computing
The Turn: Integration of Information Seeking and Retrieval in Context (The Information Retrieval Series)
TREC: Experiment and Evaluation in Information Retrieval (Digital Libraries and Electronic Publishing)
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
A survey on context-aware systems
International Journal of Ad Hoc and Ubiquitous Computing
Context revisited: a brief survey of research in context aware multimedia systems
Proceedings of the 3rd international conference on Mobile multimedia communications
The automatic creation of literature abstracts
IBM Journal of Research and Development
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Users are finding themselves interacting with increasingly complex software systems and expanding information resources. However many of these systems have little to no awareness of the personally-understood user context which expresses why they are being used. In this paper we propose a framework for modelling and proactively retrieving previously accessed and created information objects and resources that are within the context of a user's current situation. We first consider theories of context to understand the discrete aspects of context that may delineate a user's composite situations. With this we develop a framework for modelling user interaction in context along with a re-configurable algorithm for making personal recommendations for desired information objects based upon the environmental, content-based and task sequence contextual similarity of the current situation to past situations. To measure the effectiveness of our approach we use a two week activity log from four real users in a preliminary lab-based evaluation methodology. Initial results suggest the framework as a static personal recommendation algorithm is effective to varying degrees during periods of interaction for users of various characteristics. Categories and Subject Descriptors: H.3.3 [Information Storage and Retrieval]: Information Search and Retrieval