Automatic text processing: the transformation, analysis, and retrieval of information by computer
Automatic text processing: the transformation, analysis, and retrieval of information by computer
Context and structure in automated full-text information access
Context and structure in automated full-text information access
Let's browse: a collaborative Web browsing agent
IUI '99 Proceedings of the 4th international conference on Intelligent user interfaces
Margin notes: building a contextually aware associative memory
Proceedings of the 5th international conference on Intelligent user interfaces
Objective and Cognitive Context
CONTEXT '99 Proceedings of the Second International and Interdisciplinary Conference on Modeling and Using Context
Context-Mediated Behavior for AI Applications
IEA/AIE '98 Proceedings of the 11th international conference on Industrial and engineering applications of artificial intelligence and expert systems: methodology and tools in knowledge-based systems
PTV: Intelligent Personalised TV Guides
Proceedings of the Seventeenth National Conference on Artificial Intelligence and Twelfth Conference on Innovative Applications of Artificial Intelligence
The lumière project: Bayesian user modeling for inferring the goals and needs of software users
UAI'98 Proceedings of the Fourteenth conference on Uncertainty in artificial intelligence
Exploiting rich context: an incremental approach to context-based web search
CONTEXT'05 Proceedings of the 5th international conference on Modeling and Using Context
Context-Oriented image retrieval
CONTEXT'05 Proceedings of the 5th international conference on Modeling and Using Context
Identifying the multiple contexts of a situation
MRC'05 Proceedings of the Second international conference on Modeling and Retrieval of Context
Dynamic context extraction in personal communication applications
CASCON '13 Proceedings of the 2013 Conference of the Center for Advanced Studies on Collaborative Research
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In order to be useful, intelligent information retrieval agents must provide their users with context-relevant information. This paper presents WordSieve, an algorithm for automatically extracting information about the context in which documents are consulted during web browsing. Using information extracted from the stream of documents consulted by the user, WordSieve automatically builds context profiles which differentiate sets of documents that users tend to access in groups. These profiles are used in a research-aiding system to index documents consulted in the current context and pro-actively suggest them to users in similar future contexts. In initial experiments on the capability to match documents to the task contexts in which they were consulted, WordSieve indexing outperformed indexing based on Term Frequency/Inverse Document Frequency, a common document indexing approach for intelligent agents in information retrieval.