Pattern recognition of subconscious underpinnings of cognition using ultrametric topological mapping of thinking and memory

Research output: Contribution to journalArticle

1 Citation (Scopus)

Abstract

The author reviews the theory and practice of determining what parts of a data set are ultrametric. He describes the potential relevance of ultrametric topology as a framework for unconscious thought processes. This view of ultrametric topology as a framework that complements metric-based, conscious, Aristotelian logical reasoning comes from the work of the Chilean psychoanalyst, Ignacio Matte Blanco. Taking text data, the author develops an algorithm for finding local ultrametricity in such data. He applies that in two case studies. The first relates to a large set of dream reports, and therefore can possibly recall traces of unconscious thought processes. The second case study uses Twitter social media, and has the aim of picking up underlying associations. The author's case studies are selective in regard to names of people and objects, and are focused in order to highlight the principle of his approach, which is one of particular pattern finding in textual data.

Original languageEnglish
Article number1
Pages (from-to)1-16
Number of pages16
JournalInternational Journal of Cognitive Informatics and Natural Intelligence
Volume8
Issue number4
DOIs
Publication statusPublished - 2014
Externally publishedYes

Fingerprint

Pattern recognition
Topology
Data storage equipment

Cite this

@article{d7f7a6b806cc4a1eb7c2bb700f51e1be,
title = "Pattern recognition of subconscious underpinnings of cognition using ultrametric topological mapping of thinking and memory",
abstract = "The author reviews the theory and practice of determining what parts of a data set are ultrametric. He describes the potential relevance of ultrametric topology as a framework for unconscious thought processes. This view of ultrametric topology as a framework that complements metric-based, conscious, Aristotelian logical reasoning comes from the work of the Chilean psychoanalyst, Ignacio Matte Blanco. Taking text data, the author develops an algorithm for finding local ultrametricity in such data. He applies that in two case studies. The first relates to a large set of dream reports, and therefore can possibly recall traces of unconscious thought processes. The second case study uses Twitter social media, and has the aim of picking up underlying associations. The author's case studies are selective in regard to names of people and objects, and are focused in order to highlight the principle of his approach, which is one of particular pattern finding in textual data.",
keywords = "Cognition, Computation, Correspondence analysis, Hierarchical clustering, Metric, Multivariate data analysis, Psychoanalysis, Social media, Text analysis, Ultrametric, Unsupervised classification",
author = "Fionn Murtagh",
year = "2014",
doi = "10.4018/ijcini.2014100101",
language = "English",
volume = "8",
pages = "1--16",
journal = "International Journal of Cognitive Informatics and Natural Intelligence",
issn = "1557-3958",
publisher = "IGI Global Publishing",
number = "4",

}

TY - JOUR

T1 - Pattern recognition of subconscious underpinnings of cognition using ultrametric topological mapping of thinking and memory

AU - Murtagh, Fionn

PY - 2014

Y1 - 2014

N2 - The author reviews the theory and practice of determining what parts of a data set are ultrametric. He describes the potential relevance of ultrametric topology as a framework for unconscious thought processes. This view of ultrametric topology as a framework that complements metric-based, conscious, Aristotelian logical reasoning comes from the work of the Chilean psychoanalyst, Ignacio Matte Blanco. Taking text data, the author develops an algorithm for finding local ultrametricity in such data. He applies that in two case studies. The first relates to a large set of dream reports, and therefore can possibly recall traces of unconscious thought processes. The second case study uses Twitter social media, and has the aim of picking up underlying associations. The author's case studies are selective in regard to names of people and objects, and are focused in order to highlight the principle of his approach, which is one of particular pattern finding in textual data.

AB - The author reviews the theory and practice of determining what parts of a data set are ultrametric. He describes the potential relevance of ultrametric topology as a framework for unconscious thought processes. This view of ultrametric topology as a framework that complements metric-based, conscious, Aristotelian logical reasoning comes from the work of the Chilean psychoanalyst, Ignacio Matte Blanco. Taking text data, the author develops an algorithm for finding local ultrametricity in such data. He applies that in two case studies. The first relates to a large set of dream reports, and therefore can possibly recall traces of unconscious thought processes. The second case study uses Twitter social media, and has the aim of picking up underlying associations. The author's case studies are selective in regard to names of people and objects, and are focused in order to highlight the principle of his approach, which is one of particular pattern finding in textual data.

KW - Cognition

KW - Computation

KW - Correspondence analysis

KW - Hierarchical clustering

KW - Metric

KW - Multivariate data analysis

KW - Psychoanalysis

KW - Social media

KW - Text analysis

KW - Ultrametric

KW - Unsupervised classification

UR - http://www.scopus.com/inward/record.url?scp=84937722592&partnerID=8YFLogxK

U2 - 10.4018/ijcini.2014100101

DO - 10.4018/ijcini.2014100101

M3 - Article

VL - 8

SP - 1

EP - 16

JO - International Journal of Cognitive Informatics and Natural Intelligence

JF - International Journal of Cognitive Informatics and Natural Intelligence

SN - 1557-3958

IS - 4

M1 - 1

ER -