The representation of polysemy through vectors: some building blocks for constructing models and applications with LSA

The problem of the multiplicity of word meanings has preoccupied so many researches from the linguistics, psychology or computational linguistic. In this paper, we revised how LSA represents the polysemous words and we explain some bias related with the meaning generation and revised some constraint-satisfaction models which introduce into the equation some dynamic mechanisms. The idea of these models is to take the amalgamated word vector from LSA and embed it into its discourse and semantic context, and by means of a dynamic mechanism, the appropriate features of it is are selected. To illustrate our arguments, we present some networks, providing evidence that polysemous words have separated representations for each sense only in presence of the linguistic context that involved it. We also present an example of how these mechanisms also contribute to support the visual heuristic searches in the visual information retrieval interfaces (VIRIs).