User interactions with everyday applications as context for just-in-time information access

By Jay Budzik, Kristian J. Hammond. International Conference on Intelligent User Interfaces, 2000

311 citations recorded by the source corpus.

Our central claim is that user interactions with everyday 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. We discuss the requirements for such systems, and develop a general architecture for systems of this type. 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. We close by describing the results of several experiments with Watson, which show it consistently provides useful information to its users.

Subfields: Computer Networks and Communications, Information Systems, Information Systems and Management

View Paper: https://www.semanticscholar.org/paper/83ee7a2b45e17f423e344fb25245d8a952244484

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In Computer Networks and Communications

In Information Systems

In Information Systems and Management

Citations in the corpus

Exploratory Search: Beyond the Query-Response Paradigm (2009, background): “Watson (Budzik and Hammond, 2000) uses contextual information in the form of text in the active document and proactively retrieves documents from distributed information repositories via a new query.”
Placing search in context: the concept revisited (2002, methodology): “The Watson project [Budzik and Hammond 2000] attaches this background information to explicit user queries, while tools like Kenjin3 automatically suggest Web sites related4 to the document being worked upon.”
Some(what) grand challenges for information retrieval (2008, unknown): “…some time now, various researchers have recognized the significance of this issue, and investigated methods for integrating IR within various task environments, so that people do not have to leave their tasks in order to have their information problems resolved (e.g. Budzik & Hammond, 2000).”
Context in Web Search. (2000, background): “This is the goal of the Watson project [11, 12, 13].”
Evaluation of contextual information retrieval effectiveness: overview of issues and research (2010, background): “…data, browsing features [92,108], eye-tracking [57], 2. bookmarks as clues for predicting user preferences [38], 3. desktop information [32] and contextual information sources like news sources (Reuters, New York Times), Blog sites and e-commerce sites [16] used for inferring the user interests.”
Methods for Evaluating Interactive Information Retrieval Systems with Users (2009, background): “, searching or writing) and fetch related articles are also in this class [41, 92].”
Tempura: Query Analysis with Structural Templates (2020, background): “While prior work describes real-world queries as potentially under-speciﬁed, terse, and context-dependent [4, 5, 18, 35], our assumption is valid here, as we focus on a subset of real-world queries: knowledge-seeking questions .”
A survey on context-aware systems (2007, methodology): “Examples for the use of logical data are the Watson Project (Budzik and Hammond, 2000) and the IntelliZap Project (Finkelstein et al., 2001) which support the user by providing relevant information due to information read out of opened web pages, documents, etc.”
TaskTracer: a desktop environment to support multi-tasking knowledge workers (2005, methodology): “In some information retrieval systems, such as Watson [4], the currently opened document is used for context to improve the accuracy of search results.”