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Approved for public release, distribution unlimited / The ability to analyze data quickly and transform it into important information is vital for information superiority. However, the amount of available data is increasing and the time to make decisions is decreasing. There is too much data for humans to sift through and filter for decision making, so computer automation is necessary. The current approach to automating data processing is to hard-code programs to parse particular data formats, but this approach is not flexible enough to handle the constantly changing data world. The Extensible Markup Language (XML) offers a partial solution by providing a syntactic standard for data exchange. The Tactical Assessment Markup Language (TAML) is an XML vocabulary for exchanging undersea warfare tactical data that provides a standard syntax for message exchange. However, the meaning or semantics of the data is unknown to the machine processing the data. The Semantic Web is a set of technologies designed to add semantic information to data for machine processing. The technologies consist of several components including a common syntax for data exchange, common semantic representation, and a common ontology language. The Resource Description Framework (RDF) is used to explicitly state the relationships between resources or entities. The Web Ontology Language (OWL) is used to build models that explicitly define the concepts and properties in a domain. Since concept definitions are written in standard languages, a variety of reasoning engines might be used to process any ontology and its corresponding data instances. Reasoning engines can also apply algorithms to the data to infer useful information and present it to decision makers. Thus there is far less need for specialty hard-coded programs or proprietary data-representation schemes to hold semantic information, since the information needed to process data is captured in an OWL ontology, itself stored in XML format for exchange between systems. Building ontologies for specific domains such as undersea warfare allows programs to understand, process, and infer new information from coherent data. Applying Semantic Web technologies to XML languages such as TAML brings the armed forces closer to a knowledge-aware Global Information Grid (GIG). / US Navy (USN) author.

吳俊華. / Thesis (M.A.)--香港中文大學硏究院哲學部. / Manuscript (cops. 2 & 3 reprint copies) / Includes bibliographical references: leaves 156-159. / Wu Junhua. / Thesis (M.A.)--Xianggang Zhong wen da xue yan jiu yuan zhe xue bu.

Chan Kin-tong. / Thesis (M.Phil.)--Chinese University of Hong Kong, 1989. / Bibliography: leaves 81-84.

It has generally been assumed that production frequency on a feature listing task measures the strength of some relationship between features and concepts. The nature of this relationship, however, has not yet been determined. This study examines the relationship between feature list production frequency and feature relevance, or informativeness. Also tested was the hypothesis, inherent in current concept theories, that different feature types bear different relationships to a given concept, and vary widely in their informativeness. An overall relationship between production frequency and relevance was found, but is attributable to significant correlations present for only a subset of the feature types under consideration. The findings contradict the predictions of two earlier studies; namely, that parts should be the most informative feature type, and that feature type informativeness should depend on the object category. These results are discussed with respect to both feature list studies, and general theories of concepts.

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This thesis is motivated by the desire to provide technological solutions to enhance human awareness in information processing tasks. The need is pressing. Paradoxically, as information piles up people become less and less aware due to perceived scarce cognitive resources. As a consequence, specialisations become ever more specialised, projects and individuals in organisations become ever more insular. Technology can enhance awareness by informing the individual about what is happening outside their speciality. Systems which can assist people in these ways need to make sense of human communication. The computer system must know about what it is that it is processing; it must follow a socio-cognitive framework and reason with it. It must compute with meanings not symbolic surface structures. The hypothesis of the thesis is that knowledge potentially useful for enhancing awareness can be derived from interactions between people using computational models based on socio-cognitive semantics. The goals are whether an appreciable approximation of conceptual spaces can be realised through semantic spaces, and whether such semantic spaces can develop representations of meaning which have the potential to enhance the awareness of users? The two thesis questions are how well the socio-cognitive framework of G¨ardenfors could be brought into operational reality, and if a bridge can be made, then what practical issues can be involved? The theory of conceptual spaces of Peter G¨ardenfors is combined with methods from cognitive science for creating geometric spaces to represent meaning. Hyperspace Analogue to Language and Latent Semantic Analysis are used as exemplars of the cognitive science algorithms. The algorithms are modified by a variety of syntactic processing schemes to overcome a paucity of data and hence lack of expressivity in representations of meaning: part-of-speech tagging, index expressions and anaphora resolution are effected and incorporated into the semantic space. The practical element of the thesis consists of five case studies. These are developed in two parts: studies describing how meaning changes and evolves in semantic spaces, and studies describing semantic space applications featuring knowledge discovery. These studies are in a variety of domains with a variety of data: online communities of interest using a mailing list, a health-based mailing list, organisational blogs, "hallway chatter", and organisational email. The data is real world utterances that provide the situational factors that cognitive systems need to answer queries and provide context. The amounts of data are significantly less than previously used by semantic space methods, hence the need for syntactic assistance. The particular problems examined in the case studies are corporate expertise management, social network discovery, tracking ebbs and flows of topics, and noticing the change in a person's sense-of-self over time. These are significantly different to those usually examined using semantic spaces. The key differentiator of this work stems from its focus on the geometrically-based computational realisation of meaning. This thesis takes semantic spaces out of the closet and into real-world information technology applications, with a roadtest in real life.

Thesis (M.A.)--Western Conservative Baptist Seminary, 1992. / Abstract. Includes bibliographical references (leaves 66-71).