Issue No.06 - June (2012 vol.18)
J. Wiles , Sch. of Inf. Technol. & Electr. Eng., Univ. of Queensland, Brisbane, QLD, Australia
DOI Bookmark: http://doi.ieeecomputersociety.org/10.1109/TVCG.2011.100
Human discourse contains a rich mixture of conceptual information. Visualization of the global and local patterns within this data stream is a complex and challenging problem. Recurrence plots are an information visualization technique that can reveal trends and features in complex time series data. The recurrence plot technique works by measuring the similarity of points in a time series to all other points in the same time series and plotting the results in two dimensions. Previous studies have applied recurrence plotting techniques to textual data; however, these approaches plot recurrence using term-based similarity rather than conceptual similarity of the text. We introduce conceptual recurrence plots, which use a model of language to measure similarity between pairs of text utterances, and the similarity of all utterances is measured and displayed. In this paper, we explore how the descriptive power of the recurrence plotting technique can be used to discover patterns of interaction across a series of conversation transcripts. The results suggest that the conceptual recurrence plotting technique is a useful tool for exploring the structure of human discourse.
time series, data visualisation, text analysis, conversation transcripts, conceptual recurrence plot technique, pattern revealing, human discourse, conceptual information, global-local pattern visualization, data stream, information visualization technique, complex time series data, point similarity measurement, term-based similarity, language modelling, text utterances, interaction pattern discovery, Data visualization, Semantics, Humans, Image color analysis, Pain, Surgery, Time series analysis, text analysis., Concept map, recurrence, concept, plotting, conversation analysis
J. Wiles, "Conceptual Recurrence Plots: Revealing Patterns in Human Discourse", IEEE Transactions on Visualization & Computer Graphics, vol.18, no. 6, pp. 988-997, June 2012, doi:10.1109/TVCG.2011.100