Systems and Means of Informatics

2025, Volume 35, Issue 4, pp 60-72

MOVEMENT, VELOCITY, AND TRAJECTORIES OF KEYWORD REPRESENTATIONS IN THE VECTOR SPACE OF THE LANGUAGE MODEL

  • M. M. Charnine
  • N. V. Somin

Abstract

A method for calculating the positions, velocities, and evolutionary trajectories of keywords in the vector space of a static language model is proposed.
The semantic distance between word vectors at times ti and t2 is defined as the cosine distance between these vectors. The rate of semantic change is calculated as the semantic distance divided by time (t2 - t1). The rate of semantic change expresses how quickly the meaning/semantics of a word, its context, position in the vector space, and semantically close words change. The method allows one to calculate the velocities and evolutionary trajectories of topics representing a set of several related keywords. To calculate the velocities and trajectories, special evolutionary labels are inserted into the analyzed source text next to the words from the topic of interest. The case of the velocities and trajectories of keywords in the field of "machine learning" obtained from the PubMed library is considered. Keyword vectors and their changes over time are calculated using the Word2Vec neural network. A semantic map is presented that allows one to visually assess evolutionary trajectories and velocities. It is based on the PCA (Principal Component Analysis) algorithm which allows one to obtain a projection of trajectories onto a two-dimensional plane.

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