This paper presents a solution to extend the IEEE LOM standard with ontology-based semantic annotations for efficient use of learning objects outside Learning Management Systems. The data model corresponding to this approach is first presented. The proposed indexing technique for this model development in order to acquire a better annotation of…

This article explores ontological principles and their potential applications in the formal description of archival photographs. Current archival descriptive practices are reviewed and the larger question is addressed: do archivists who are engaged in describing photographs need a more formalized system of representation, or do existing encoding…

Discussion of the failure of individual keywords to identify conceptual content of documents in retrieval systems highlights Metric Similarity Modeling, a method for creating vector space representation of documents based on modeling target interdocument similarity values. Semantic relatedness, latent semantic indexing, an indexing and retrieval…

Describes a new method for automatic indexing and retrieval called latent semantic indexing (LSI). Problems with matching query words with document words in term-based information retrieval systems are discussed, semantic structure is examined, singular value decomposition (SVD) is explained, and the mathematics underlying the SVD model is…

The first part of this dissertation is a metatheoretical discussion of the needs and means of semantic analysis. This discussion includes sections on metalanguage, deep and surface structure and structural semantics, and procedures for relating the English of abstracts to a classification concordance in the same language. The second part describes…

Describes the Belief Function Model for automatic indexing and ranking of documents which is based on a controlled vocabulary and on term frequencies in each document. Belief Function Theory is explained, and the Belief Function Model is compared to the Standard Vector Space Model. (17 references) (LRW)