A vector field approach to lexical semantics

Peter Wittek, Sándor Darányi, Ying Hsang Liu

Research output: Chapter in Book/Report/Conference proceedingConference contributionpeer-review

3 Citations (Scopus)

Abstract

We report work in progress on measuring “forces” underlying the semantic drift by comparing it with plate tectonics in geology. Based on a brief survey of energy as a key concept in machine learning, and the Aristotelian concept of potentiality vs. actuality allowing for the study of energy and dynamics in language, we propose a field approach to lexical analysis. Until evidence to the contrary, it was assumed that a classical field in physics is appropriate to model word semantics. The approach used the distributional hypothesis to statistically model word meaning.We do not address the modelling of sentence meaning here. The computability of a vector field for the indexing vocabulary of the Reuters- 21578 test collection by an emergent self-organizing map suggests that energy minima as learnables in machine learning presuppose concepts as energy minima in cognition. Our finding needs to be confirmed by a systematic evaluation.

Original languageEnglish
Title of host publicationQuantum Interaction - 8th International Conference, QI 2014, Revised Selected Papers
EditorsKirsty Kitto, Claudia Bergomi, Thomas Filk, Harald Atmanspacher
PublisherSpringer Verlag
Pages78-89
Number of pages12
ISBN (Electronic)9783319159300
DOIs
Publication statusPublished - 2015
Externally publishedYes
Event8th International Conference on Quantum Interaction, QI 2014 - Filzbach, Switzerland
Duration: 30 Jun 20143 Jul 2014

Publication series

NameLecture Notes in Computer Science (including subseries Lecture Notes in Artificial Intelligence and Lecture Notes in Bioinformatics)
Volume8951
ISSN (Print)0302-9743
ISSN (Electronic)1611-3349

Conference

Conference8th International Conference on Quantum Interaction, QI 2014
Country/TerritorySwitzerland
CityFilzbach
Period30/06/143/07/14

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