Darányi, S.; Wittek, P.: Demonstrating conceptual dynamics in an evolving text collection (2013)
0.01
0.0065615685 = product of:
0.024059083 = sum of:
0.0058576106 = weight(_text_:a in 1137) [ClassicSimilarity], result of:
0.0058576106 = score(doc=1137,freq=18.0), product of:
0.030653298 = queryWeight, product of:
1.153047 = idf(docFreq=37942, maxDocs=44218)
0.026584605 = queryNorm
0.19109234 = fieldWeight in 1137, product of:
4.2426405 = tf(freq=18.0), with freq of:
18.0 = termFreq=18.0
1.153047 = idf(docFreq=37942, maxDocs=44218)
0.0390625 = fieldNorm(doc=1137)
0.0024550997 = weight(_text_:s in 1137) [ClassicSimilarity], result of:
0.0024550997 = score(doc=1137,freq=4.0), product of:
0.028903782 = queryWeight, product of:
1.0872376 = idf(docFreq=40523, maxDocs=44218)
0.026584605 = queryNorm
0.08494043 = fieldWeight in 1137, product of:
2.0 = tf(freq=4.0), with freq of:
4.0 = termFreq=4.0
1.0872376 = idf(docFreq=40523, maxDocs=44218)
0.0390625 = fieldNorm(doc=1137)
0.015746372 = weight(_text_:u in 1137) [ClassicSimilarity], result of:
0.015746372 = score(doc=1137,freq=2.0), product of:
0.08704981 = queryWeight, product of:
3.2744443 = idf(docFreq=4547, maxDocs=44218)
0.026584605 = queryNorm
0.1808892 = fieldWeight in 1137, product of:
1.4142135 = tf(freq=2.0), with freq of:
2.0 = termFreq=2.0
3.2744443 = idf(docFreq=4547, maxDocs=44218)
0.0390625 = fieldNorm(doc=1137)
0.27272728 = coord(3/11)
- Abstract
- Based on real-world user demands, we demonstrate how animated visualization of evolving text corpora displays the underlying dynamics of semantic content. To interpret the results, one needs a dynamic theory of word meaning. We suggest that conceptual dynamics as the interaction between kinds of intellectual and emotional content and language is key for such a theory. We demonstrate our method by two-way seriation, which is a popular technique to analyze groups of similar instances and their features as well as the connections between the groups themselves. The two-way seriated data may be visualized as a two-dimensional heat map or as a three-dimensional landscape in which color codes or height correspond to the values in the matrix. In this article, we focus on two-way seriation of sparse data in the Reuters-21568 test collection. To achieve a meaningful visualization, we introduce a compactly supported convolution kernel similar to filter kernels used in image reconstruction and geostatistics. This filter populates the high-dimensional sparse space with values that interpolate nearby elements and provides insight into the clustering structure. We also extend two-way seriation to deal with online updates of both the row and column spaces and, combined with the convolution kernel, demonstrate a three-dimensional visualization of dynamics.
- Source
- Journal of the American Society for Information Science and Technology. 64(2013) no.12, S.2564-2572
- Theme
- Semantisches Umfeld in Indexierung u. Retrieval
- Type
- a