Introduces this special issue which describes several approaches to semantic knowledge representations. Discusses the various quantitative procedures employed in the articles, noting that they can also serve as theoretical approaches to knowledge representation. (SR)

Describes a computational model of high-dimensional context space: the Hyperspace Analog to Language (HAL). Shows that HAL provides sufficient information to make semantic, grammatical, and abstract distinctions. Demonstrates the cognitive compatibility of the representations with human processing; and introduces a new methodology that extracts…

Offers an introduction to the theory and implementation of Latent Semantic Analysis (LSA), a theory and method for extracting and representing the contextual-usage meaning of words by statistical computations applied to a large corpus of text. Gives an overview of applications and modeling of human knowledge to which LSA has been applied. (SR)

Introduces the Knowledge Digraph Contribution (KDC) data-analysis methodology for quantitatively measuring the degree to which a given knowledge digraph can account for the occurrence of specific sequences of propositions in recall, summarization, talk-aloud and question-answering protocol data. Notes the applicability of this approach to the…

Illustrates use of Latent Semantic Analysis (LSA) for predicting coherence through reanalyzing two studies that manipulated coherence of texts and assessed readers' comprehension. Finds that LSA predicts effects of text coherence on comprehension. Notes that LSA can be applied as an automated method that produces coherence predictions similar to…