234 research outputs found
Ultrametric embedding: application to data fingerprinting and to fast data clustering
We begin with pervasive ultrametricity due to high dimensionality and/or
spatial sparsity. How extent or degree of ultrametricity can be quantified
leads us to the discussion of varied practical cases when ultrametricity can be
partially or locally present in data. We show how the ultrametricity can be
assessed in text or document collections, and in time series signals. An aspect
of importance here is that to draw benefit from this perspective the data may
need to be recoded. Such data recoding can also be powerful in proximity
searching, as we will show, where the data is embedded globally and not locally
in an ultrametric space.Comment: 14 pages, 1 figure. New content and modified title compared to the 19
May 2006 versio
Between the Information Economy and Student Recruitment: Present Conjuncture and Future Prospects
In university programs and curricula, in general we react to the need to meet
market needs. We respond to market stimulus, or at least try to do so. Consider
now an inverted view. Consider our data and perspectives in university programs
as reflecting and indeed presaging economic trends. In this article I pursue
this line of thinking. I show how various past events fit very well into this
new view. I provide explanation for why some technology trends happened as they
did, and why some current developments are important now.Comment: 18 pages, 4 figure
The Haar Wavelet Transform of a Dendrogram: Additional Notes
We consider the wavelet transform of a finite, rooted, node-ranked, -way
tree, focusing on the case of binary () trees. We study a Haar wavelet
transform on this tree. Wavelet transforms allow for multiresolution analysis
through translation and dilation of a wavelet function. We explore how this
works in our tree context.Comment: 37 pp, 1 fig. Supplementary material to "The Haar Wavelet Transform
of a Dendrogram", http://arxiv.org/abs/cs.IR/060810
Origins of Modern Data Analysis Linked to the Beginnings and Early Development of Computer Science and Information Engineering
The history of data analysis that is addressed here is underpinned by two
themes, -- those of tabular data analysis, and the analysis of collected
heterogeneous data. "Exploratory data analysis" is taken as the heuristic
approach that begins with data and information and seeks underlying explanation
for what is observed or measured. I also cover some of the evolving context of
research and applications, including scholarly publishing, technology transfer
and the economic relationship of the university to society.Comment: 26 page
Pattern recognition in narrative: Tracking emotional expression in context
Using geometric data analysis, our objective is the analysis of narrative, with narrative of emotion being the focus in this work. The following two principles for analysis of emotion inform our work. Firstly, emotion is revealed not as a quality in its own right but rather through interaction. We study the 2-way relationship of Ilsa and Rick in the movie Casablanca, and the 3-way relationship of Emma, Charles and Rodolphe in the novel {\em Madame Bovary}. Secondly, emotion, that is expression of states of mind of subjects, is formed and evolves within the narrative that expresses external events and (personal, social, physical) context. In addition to the analysis methodology with key aspects that are innovative, the input data used is crucial. We use, firstly, dialogue, and secondly, broad and general description that incorporates dialogue. In a follow-on study, we apply our unsupervised narrative mapping to data streams with very low emotional expression. We map the narrative of Twitter streams. Thus we demonstrate map analysis of general narratives
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