Search (4 results, page 1 of 1)

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Abstract

Granularity is a novel concept for presenting information in search result interfaces of hierarchical query-driven information retrieval systems in a manner that can support understanding and exploration of the context of the retrieved information (e.g., by highlighting its position in the granular hierarchy and exposing its relationship with relatives in the hierarchy). Little research, however, has been conducted on the effects of granularity of search results on the relevance judgment behavior of engineers. Engineers are highly motivated information users who are particularly interested in understanding the context of the retrieved information. Therefore, it is hypothesized that the design of systems with careful regard for granularity would improve engineers' relevance judgment behavior. To test this hypothesis, a prototype system was developed and evaluated in terms of the time needed for users to find relevant information, the accuracy of their relevance judgment, and their subjective satisfaction. To evaluate the prototype, a user study was conducted where participants were asked to complete tasks, complete a satisfaction questionnaire, and be interviewed. The findings showed that participants performed better and were more satisfied when the prototype system presented only relevant information in context. Although this study presents some novel findings about the effects of granularity and context on user relevance judgment behavior, the results should be interpreted with caution. For example, participants in this research were recruited by convenience and performed a set of simulated tasks as opposed to real ones. However, suggestions for further research are presented.

Source

Journal of the American Society for Information Science and Technology. 61(2010) no.3, S.453-467

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Abstract

Eye movement data can provide an in-depth view of human reasoning and the decision-making process, and modern information retrieval (IR) research can benefit from the analysis of this type of data. The aim of this research was to examine the relationship between relevance criteria use and visual behavior in the context of predictive relevance judgments. To address this objective, a multimethod research design was employed that involved observation of participants' eye movements, talk-aloud protocols, and postsearch interviews. Specifically, the results reported in this article came from the analysis of 281 predictive relevance judgments made by 24 participants using the Google search engine. We present a novel stepwise methodological framework for the analysis of relevance judgments and eye movements on the Web and show new patterns of relevance criteria use during predictive relevance judgment. For example, the findings showed an effect of ranking order and surrogate components (Title, Summary, and URL) on the use of relevance criteria. Also, differences were observed in the cognitive effort spent between very relevant and not relevant judgments. We conclude with the implications of this study for IR research.

Source

Journal of the American Society for Information Science and Technology. 63(2012) no.9, S.1728-1746

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Series

Communications in computer and information science; 478

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Series

Communications in computer and information science; 544