English (United Kingdom)

https://curated-unify.zendy.io/wp-json/zendy-region/v1/featured_content/oa?rat=en

https://curated-unify.zendy.io/wp-json/zendy-region/v1/highlighted_journal/

Global: Zendy Plus annual

Presents the access of premium content as premium feature

Premium Content

Presents the keyphrase highlighting as premium feature

Keyphrase Highlighting

Presents the summarisation as premium feature

Summarisation

Insights

Presents the pdf analysis as premium feature

PDF Analysis

Presents the zaia usage as premium feature

ZAIA

Global: Zendy Plus monthly

Global: Zendy Tools annual

Global: Zendy Tools monthly

Global: Zendy Free Plan

Techniques in which words are represented as vectors have proved useful inmany applications in computational linguistics, however there is currently nogeneral semantic formalism for representing meaning in terms of vectors. Wepresent a framework for natural language semantics in which words, phrases andsentences are all represented as vectors, based on a theoretical analysis whichassumes that meaning is determined by context.  In the theoretical analysis, we define a corpus model as a mathematicalabstraction of a text corpus. The meaning of a string of words is assumed to bea vector representing the contexts it occurs in in the corpus model. Based onthis assumption, we can show that the vector representations of words can beconsidered as elements of an algebra over a field. We note that in applicationsof vector spaces to representing meanings of words there is an underlyinglattice structure; we interpret the partial ordering of the lattice asdescribing entailment between meanings. We also define the context-theoreticprobability of a string, and, based on this and the lattice structure, a degreeof entailment between strings.  Together these properties form guidelines as to how to construct semanticrepresentations within the framework. A context theory is an implementation ofthe framework; in an implementation strings are represented as vectors with theproperties deduced from the theoretical analysis.  We show how to incorporate logical semantics into context theories; thisenables us to represent statistical information about uncertainty by takingweighted sums of individual representations. We also use the framework toanalyse approaches to the task of recognising textual entailment, toontological representations of meaning and to representing syntactic structure.For the latter, we give new algebraic descriptions of link grammar.

Context-theoretic Semantics for Natural Language: an Algebraic Framework