.png){kind=icon}
Return
Information access in context
.png){kind=icon}
PRE
AI
DOI：10.1016/S0950-7051(00)00105-2.png)
.png){kind=icon}
Original request for help.png){kind=icon}
Share.png){kind=icon}
Save
Abstract
En 中文
Our central claim is that user interactions with productivity applications (e.g, word processors, Web browsers, etc.) provide rich contextual information that can be leveraged to support just-in-time access to task-relevant information. As evidence for our claim, we present Watson, a system which gathers contextual information in the form of the text of the document the user is manipulating, in order to proactively retrieve documents from distributed information repositories related to task at hand, as well as process explicit requests in the context of this task. We close by describing the results of several experiments with Watson, which show it consistently provides useful information to its users. The experiments also suggest that, contrary to the assumptions of many system designers, similar documents are not necessarily useful documents in the context of a particular task. (C) 2001 Elsevier Science B.V. All rights reserved.
Keywords:
information access
agents
context
proactive systems
automated resource discovery
similarity
AI Summary
Key information extracted from the uploaded paper, including a brief overview, abstract, background, key highlights, visual analysis, and future outlook.
Journal
K
IF:
7.6
Papers:
1.3W
Citations:
4.5W
Organization
No organization information available
Cited Papers
.png){kind=icon}
ShareSaveShareSaveCarbonization of Carboxylate‐Functionalized Polymers of Intrinsic Microporosity for Water Treatment
PREAI
ShareSaveShareSaveShareSaveShareSave
View more