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  • × author_ss:"Greisdorf, H."
  • × author_ss:"O'Connor, B."
  1. Greisdorf, H.; O'Connor, B.: Modelling what users see when they look at images : a cognitive viewpoint (2002) 0.00 
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    Abstract
    Analysis of user viewing and query-matching behavior furnishes additional evidence that the relevance of retrieved images for system users may arise from descriptions of objects and content-based elements that are not evident or not even present in the image. This investigation looks at how users assign pre-determined query terms to retrieved images, as well as looking at a post-retrieval process of image engagement to user cognitive assessments of meaningful terms. Additionally, affective/emotion-based query terms appear to be an important descriptive category for image retrieval. A system for capturing (eliciting) human interpretations derived from cognitive engagements with viewed images could further enhance the efficiency of image retrieval systems stemming from traditional indexing methods and technology-based content extraction algorithms. An approach to such a system is posited.
    Type
    a
  2. Greisdorf, H.; O'Connor, B.: Nodes of topicality modeling user notions of on topic documents (2003) 0.00 
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    Abstract
    Griesdorf and O'Connor attempt to determine the aspects of a retrieved item that provide a questioner with evidence that the item is in fact on the topic searched independent of its relevance. To this end they collect data from 32 participants, 11 from the business community as well as 21 doctoral students at the University of North Texas each of whom were asked to state if they considered material that approaches a topic in each of 14 specific manners as " on topic" or "off topic." Chi-square indicates that the observed values are significantly different from expected values and the chi-square residuals for on topic judgements exceed plus or minus two in eight cases and plus two in five cases. The positive values which indicate a percentage of response greater than that from chance suggest that documents considered topical are only related to the problem at hand, contain terms that were in the query, and describe, explain or expand the topic of the query. The chi-square residuals for off topic judgements exceed plus or minus two in ten cases and plus two in four cases. The positive values suggest that documents considered not topical exhibit a contrasting, contrary, or confounding point of view, or merely spark curiosity. Such material might well be relevant, but is not judged topical. This suggests that topical appropriateness may best be achieved using the Bruza, et alia, left compositional monotonicity approach.
    Type
    a

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