Greisdorf, H.; O'Connor, B.: Modelling what users see when they look at images : a cognitive viewpoint (2002)
0.00
8.9242304E-4 = product of:
0.005354538 = sum of:
0.005354538 = weight(_text_:in in 4471) [ClassicSimilarity], result of:
0.005354538 = score(doc=4471,freq=2.0), product of:
0.059380736 = queryWeight, product of:
1.3602545 = idf(docFreq=30841, maxDocs=44218)
0.043654136 = queryNorm
0.09017298 = fieldWeight in 4471, product of:
1.4142135 = tf(freq=2.0), with freq of:
2.0 = termFreq=2.0
1.3602545 = idf(docFreq=30841, maxDocs=44218)
0.046875 = fieldNorm(doc=4471)
0.16666667 = coord(1/6)
- 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.