Vectors and matrices: word meaning for advanced access

Title:

Vectors and matrices: word meaning for advanced access

Access Right:

Open Access

Created on:

09/04/2020

Language:

English

Keywords:

Discovery

Contributor:

Preserveware Editor

Date:

14/05/2017

Metrics:

683 views , 1 Downloads
Introduction into the core ideas to represent word meaning by vectors, including a respective match between linguistics and information science.

Expected learning outcomes

  • Understand the difference between vectors, matrices, vector space, vector field.
  • Understand bicomponential theories of word meaning.
  • Get a grasp of term weighting to distribute content in vector space.
  • See the link between distributed content vs. lexical fields in semantics.

What is the target audience?

  • Digital Preservation and Digital Humanities practitioners who are interested in investigating the deployment of semantics and relevant cutting-edge technologies.
  • Researchers working on semantics who are interested in investigating the application of relevant methods and technologies in a Humanities field.

Level of advancement/ prerequisites

Intermediate

Material chapters

This recorded lecture is part of a larger module “Dynamics of knowledge organisation”: http://pericles-project.eu/training-module/dynamics-of-knowledge-organisation/

This is chapter 2 of the complete set:

  1. Semantics and DP: basic concepts, theories and trends
  2. Vectors and matrices: word meaning for advanced access
  3. Vector fields: a new approach to evolving semantics
  4. The Semantic Web & the Emergence of Ontologies
  5. Semantic Technologies & DP
  6. Evolving Semantics: Ontology Evolution & Semantic Drifts

Time required for completion

25 min

​Supplementary reading

Turney and Pantel’s paper is a very good overview of how word meaning can be captured by contextualized index term occurrence and co-occurrence frequencies. At the same time, being a review article, it is also technical and requires a level of technical understanding and the ability to generalize.

Turney, P.D., Pantel, P. 2010. From Frequency to Meaning: Vector Space Models of Semantics.Journal of Artificial Intelligence Research (37), 141-188.

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