SKOS concepts and natural language concepts: An analysis of latent relationships in KOSs

Abstract

The vehicle to represent Knowledge Organization Systems (KOSs) in the environment of the Semantic Web and linked data is the Simple Knowledge Organization System (SKOS). SKOS provides a way to assign a URI to each concept, and this URI functions as a surrogate for the concept. This fact makes of main concern the need to clarify the URIs' ontological meaning. The aim of this study is to investigate the relation between the ontological substance of KOS concepts and concepts revealed through the grammatical and syntactic formalisms of natural language. For this purpose, we examined the dividableness of concepts in specific KOSs (i.e. a thesaurus, a subject headings system and a classification scheme) by applying Natural Language Processing (NLP) techniques (i.e. morphosyntactic analysis) to the lexical representations (i.e. RDF literals) of SKOS concepts. The results of the comparative analysis reveal that, despite the use of multi-word units, thesauri tend to represent concepts in a way that can hardly be further divided conceptually, while Subject Headings and Classification Schemes -to a certain extent -comprise terms that can be decomposed into more conceptual constituents. Consequently, SKOS concepts deriving from thesauri are more likely to represent atomic conceptual units and thus be more appropriate tools for inference and reasoning. Since identifiers represent the meaning of a concept, complex concepts are neither the most appropriate nor the most efficient way of modelling a KOS for the Semantic Web.

Expressiveness and machine processability of Knowledge Organization Systems (KOS): an analysis of concepts and relations

“…There follows a more detailed and comparative analysis concerning the expressiveness of KOSs. In a previous study [61] we defined two categories of concepts, namely atomic and complex, based on linguistic criteria which were quantified following the morphosyntactic analysis of KOSs. Briefly, atomic concepts are the conceptually undividable units as perceived in the natural language context; into this category also fall the compounds which are terms that can be split morphologically into separate components (words), like the LCSH heading "Hours of labor", yet the term as a whole represents a single concept.…”

Identifying Authorship from Linguistic Text Patterns

“…Approaches to dealing with corpus of texts usually include natural language parsing techniques [8]. Although this research is primarily built upon the information systems literature, it also builds upon work in computer science, literary criticism and computational linguistics [34]. This is largely due to the influence of Zipf's law, an algorithm explaining frequency patterns within a group of phenomenon as diverse as word frequency, the distribution of city size and the distribution of income [48] [26][25] [45].…”

“…Mastora et al [34] argue that "Natural language is both fundamental and complicated as a communication system; therefore, it has been the subject of many disciplines" and that it has "rules, norms and patterns concerning its morphology and syntax" (pg. 496).…”

“…Big Data analysis techniques, including text analysis and text mining, have grown and enable faster and more precise understanding of large volumes of text than previously possible. Linguistic factors for analyzing text have also progressively become more important, although less adopted, in information systems research, than in other fields such as computational linguistics and human-computer interaction [34]. New methods for analyzing text have resulted in increasing quantification of large bodies of text (e.g., counts of numbers of terms) [21][22] [39].…”

The support of constructs in thesaurus tools from a Semantic Web perspective: Framework to assess standard conformance

“…Thesauri add to information systems the ability to offer navigation through a thesaurus' categories or to retrieve documents that have been classified under one of its categories. Moreover, the Semantic Web and linked data have brought about a renewed interest in thesauri as conceptual tools that can be used to improve semantic interoperability [1][2][3][4]. Their potential as support for concept-based searches, i.e., searches in which the user looks for concepts instead of terms in document content [1,4,5] is a valuable feature in the Semantic Web context.…”