Ultrametric Component Analysis with Application to Analysis of Text and of Emotion

We review the theory and practice of determining what parts of a data set are ultrametric. It is assumed that the data set, to begin with, is endowed with a metric, and we include discussion of how this can be brought about if a dissimilarity, only, holds. The basis for part of the metric-endowed data set being ultrametric is to consider triplets of the observables (vectors). We develop a novel consensus of hierarchical clusterings. We do this in order to have a framework (including visualization and supporting interpretation) for the parts of the data that are determined to be ultrametric. Furthermore a major objective is to determine locally ultrametric relationships as opposed to non-local ultrametric relationships. As part of this work, we also study a particular property of our ultrametricity coefficient, namely, it being a function of the difference of angles of the base angles of the isosceles triangle. This work is completed by a review of related work, on consensus hierarchies, and of a major new application, namely quantifying and interpreting the emotional content of narrative.Comment: 49 pages, 15 figures, 52 citation

Visualization of Jacques Lacan’s Registers of the Psychoanalytic Field, and Discovery of Metaphor and of Metonymy. Analytical Case Study of Edgar Allan Poe’s “The Purloined Letter”

We start with a description of Lacan’s work that we then take into our analytics methodology. In a first investigation, a Lacan-motivated template of the Poe story is fitted to the data. A segmentation of the storyline is used in order to map out the diachrony. Based on this, it will be shown how synchronous aspects, potentially related to Lacanian registers, can be sought. This demonstrates the effectiveness of an approach based on a model template of the storyline narrative. In a second and more comprehensive investigation, we develop an approach for revealing, that is, uncovering, Lacanian register relationships. Objectives of this work include the wide and general application of our methodology. This methodology is strongly based on the “letting the data speak” Correspondence Analysis analytics platform of Jean-Paul Benzécri, that is also the geometric data analysis, both qualitative and quantitative analytics, developed by Pierre Bourdieu

Core Conflictual Relationship

Following detailed presentation of the Core Conflictual Relationship Theme (CCRT), there is the objective of relevant methods for what has been described as verbalization and visualization of data. Such is also termed data mining and text mining, and knowledge discovery in data. The Correspondence Analysis methodology, also termed Geometric Data Analysis, is shown in a case study to be comprehensive and revealing. Quite innovative here is how the analysis process is structured. For both illustrative and revealing aspects of the case study here, relatively extensive dream reports are used. The dream reports are from an open source repository of dream reports, and the current  study proposes a possible framework for the analysis of dream report narratives, and  further, how such an analysis could be relevant within the psychotherapeutic context. This Geometric Data Analysis here confirms the validity of CCRT method

Market structures in arts and entertainment

Marketing arts and entertainment is a challenge. Consumers may buy the same groceries every week, but when it comes to arts and entertainment, people usually want something different from last time. The result: a vast, constantly changing choice of books, cd's, movies, performances and shows to meet this need for variety and novelty. But how do you help consumers find their way in this plethora of options? Who do you approach when you have a new performance to sell every night, but don't want to inundate your customers with direct mail? How do you compose attractive subscription packages that help you get a head start in filling the house? Since recently, many cultural organizations have new, advanced transaction data systems that record individual buying histories. Modern theater box office systems link a customer id and address with each transaction; library loan systems track the borrowing behavior of patrons to ensure the timely return of books; and in The Netherlands, the visiting behavior of National Museum Card holders is logged electronically on central servers to aid reimbursement to participating museums. We show how these transaction data may help in understanding who likes what: what types of arts and entertainment consumers are there and what types of products do they like? Armed with such insights, marketers may be more effective in composing the right subscription packages, in selecting the right direct mail prospects or in designing the right presentation for the abundance and variety of choice.Wedel, M. [Promotor]Frambach, R.T. [Copromotor

Exploring Language Mechanisms: The Mass-Count Distinction and The Potts Neural Network

The aim of this thesis is to explore language mechanisms in two aspects. First, the statistical properties of syntax and semantics, and second, the neural mechanisms which could be of possible use in trying to understand how the brain learns those particular statistical properties. In the first part of the thesis (part A) we focus our attention on a detailed statistical study of the syntax and semantics of the mass-count distinction in nouns. We collected a database of how 1,434 nouns are used with respect to the mass-count distinction in six languages; additional informants characterised the semantics of the underlying concepts. Results indicate only weak correlations between semantics and syntactic usage. The classification rather than being bimodal, is a graded distribution and it is similar across languages, but syntactic classes do not map onto each other, nor do they reflect, beyond weak correlations, semantic attributes of the concepts. These findings are in line with the hypothesis that much of the mass/count syntax emerges from language- and even speaker-specific grammaticalisation. Further, in chapter 3 we test the ability of a simple neural network to learn the syntactic and semantic relations of nouns, in the hope that it may throw some light on the challenges in modelling the acquisition of the mass-count syntax. It is shown that even though a simple self-organising neural network is insufficient to learn a mapping implementing a syntactic- semantic link, it does however show that the network was able to extract the concept of 'count', and to some extent that of \u2018mass\u2019 as well, without any explicit definition, from both the syntactic and from the semantic data. The second part of the thesis (part B) is dedicated to studying the properties of the Potts neural network. The Potts neural network with its adaptive dynamics represents a simplified model of cortical mechanisms. Among other cognitive phenomena, it intends to model language production by utilising the latching behaviour seen in the network. We expect that a model of language processing should robustly handle various syntactic- semantic correlations amongst the words of a language. With this aim, we test the effect on storage capacity of the Potts network when the memories stored in it share non trivial correlations. Increase in interference between stored memories due to correlations is studied along with modifications in learning rules to reduce the interference. We find that when strongly correlated memories are incorporated in the storage capacity definition, the network is able to regain its storage capacity for low sparsity. Strong correlations also affect the latching behaviour of the Potts network with the network unable to latch from one memory to another. However latching is shown to be restored by modifying the learning rule. Lastly, we look at another feature of the Potts neural network, the indication that it may exhibit spin-glass characteristics. The network is consistently shown to exhibit multiple stable degenerate energy states other than that of pure memories. This is tested for different degrees of correlations in patterns, low and high connectivity, and different levels of global and local noise. We state some of the implications that the spin-glass nature of the Potts neural network may have on language processing

Comparative Analysis of Student Learning: Technical, Methodological and Result Assessing of PISA-OECD and INVALSI-Italian Systems .

PISA is the most extensive international survey promoted by the OECD in the field of education, which measures the skills of fifteen-year-old students from more than 80 participating countries every three years. INVALSI are written tests carried out every year by all Italian students in some key moments of the school cycle, to evaluate the levels of some fundamental skills in Italian, Mathematics and English. Our comparison is made up to 2018, the last year of the PISA-OECD survey, even if INVALSI was carried out for the last edition in 2022. Our analysis focuses attention on the common part of the reference populations, which are the 15-year-old students of the 2nd class of secondary schools of II degree, where both sources give a similar picture of the students

Biodiversity Conservation and Phylogenetic Systematics: Preserving our evolutionary heritage in an extinction crisis

Biodiversity; Nature conservatio