Zhang, J.; An, L.; Tang, T.; Hong, Y.: Visual health subject directory analysis based on users' traversal activities (2009)
0.02
0.016922247 = product of:
0.05922786 = sum of:
0.03555402 = weight(_text_:u in 3112) [ClassicSimilarity], result of:
0.03555402 = score(doc=3112,freq=4.0), product of:
0.11581901 = queryWeight, product of:
3.2744443 = idf(docFreq=4547, maxDocs=44218)
0.035370585 = queryNorm
0.30697915 = fieldWeight in 3112, product of:
2.0 = tf(freq=4.0), with freq of:
4.0 = termFreq=4.0
3.2744443 = idf(docFreq=4547, maxDocs=44218)
0.046875 = fieldNorm(doc=3112)
0.023673838 = weight(_text_:j in 3112) [ClassicSimilarity], result of:
0.023673838 = score(doc=3112,freq=2.0), product of:
0.11238991 = queryWeight, product of:
3.1774964 = idf(docFreq=5010, maxDocs=44218)
0.035370585 = queryNorm
0.21064025 = fieldWeight in 3112, product of:
1.4142135 = tf(freq=2.0), with freq of:
2.0 = termFreq=2.0
3.1774964 = idf(docFreq=5010, maxDocs=44218)
0.046875 = fieldNorm(doc=3112)
0.2857143 = coord(2/7)
- Abstract
- Concerns about health issues cover a wide spectrum. Consumer health information, which has become more available on the Internet, plays an extremely important role in addressing these concerns. A subject directory as an information organization and browsing mechanism is widely used in consumer health-related Websites. In this study we employed the information visualization technique Self-Organizing Map (SOM) in combination with a new U-matrix algorithm to analyze health subject clusters through a Web transaction log. An experimental study was conducted to test the proposed methods. The findings show that the clusters identified from the same cells based on path-length-1 outperformed both the clusters from the adjacent cells based on path-length-1 and the clusters from the same cells based on path-length-2 in the visual SOM display. The U-matrix method successfully distinguished the irrelevant subjects situated in the adjacent cells with different colors in the SOM display. The findings of this study lead to a better understanding of the health-related subject relationship from the users' traversal perspective.
