Activity-Based Query Refinement for Context-Aware Information Retrieval

Humans are quite successful at conveying ideas to each other and retrieving information from interactions appropriately. This is due to many factors: the richness of the language they share, the common understanding of how the world works, and an implicit understanding of everyday situations (Dey & Abowd, 1999). When humans talk with humans, they are able to use implicit situational information (i.e., context) to enhance the information exchange process. Context (Cool & Spink, 2002) plays a vital part in adaptive and personalized information retrieval and access. Unfortunately, computer communications lacks this ability to provide auxiliary context in addition to the substantial content of information. As computers are becoming more and more ubiquitous and mobile, there is a need and possibility to provide information “personalized, any time, and anywhere” (ITU, 2006). In these scenarios, large amounts of information circulate in order to create smart and proactive environments that will significantly enhance both the work and leisure experiences of people. Context-awareness plays an important role to enable personalized information retrieval and access according to the current situation with minimal human intervention. Although context-aware information retrieval systems have been researched for a decade (Korkea-aho, 2000), the rise of mobile and ubiquitous computing put new challenges to issue, and therefore we are motivated to come up with new solutions to achieve non-intrusive, personalized information access on the mobile service platforms and heterogeneous wireless environments.

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An Investigation of User Behaviour Consistency for Context-Aware Information Retrieval Systems

International Journal of Advanced Pervasive and Ubiquitous Computing ◽

10.4018/japuc.2009100105 ◽

2009 ◽

Vol 1 (4) ◽

pp. 69-90 ◽

Cited By ~ 1

Author(s):

Adam Grzywaczewski ◽

Rahat Iqbal ◽

Anne James ◽

John Halloran

Keyword(s):

Information Retrieval ◽

User Study ◽

User Interaction ◽

Context Aware ◽

Interaction Patterns ◽

Frequent User ◽

User Interactions ◽

Information Retrieval Systems ◽

Finite Set ◽

Domain Expertise

Users interact with the Internet in dynamic environments that require the IR system to be context aware. Modern IR systems take advantage of user location, browsing history or previous interaction patterns, but a significant number of contextual factors that impact the user information retrieval process are not yet available. Parameters like the emotional state of the user and user domain expertise affect the user experience significantly but are not understood by IR systems. This article presents results of a user study that simplifies the way context in IR and its role in the systems’ efficiency is perceived. The study supports the hypothesis that the number of user interaction contexts and the problems that a particular user is trying to solve is related to lifestyle. Therefore, the IR system’s perception of the interaction context can be reduced to a finite set of frequent user interactions.

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