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No / In her recent publication, Haraway (Haraway, D., (2003). The companion species manifesto: dogs, people, and significant otherness. Chicago, Prickly Paradigm Press.) extends her concept of the cyborg to explore how the figure of ¿companion species¿ can rethink the models of reality that traditionally underpin cultural research. This paper investigates the kind of consumption worlds and consumption relations the ontology of companion species suggests and what it offers in terms of understanding consumption in a post-human (and post-canine) consumer-behavior landscape. Following this, it proposes the concept of ¿companion-species consumption¿ (CSC) as a new ontology to extend interpretive research on consumers and their pets (Hirschman, E. C., (1994). Consumers and their animal companions. J Consum Res, 20 (3), 616¿632.; Holbrook, M.B., Stephens, D.L., Day, E., Holbrook, S.M. and Strazar, G., (2001). A collective stereographic photo essay on key aspects of animal companionship: the truth about dogs and cats. Academy of Marketing Science Review 1; AMS.; Belk, Russell W., (1996). Metaphoric relationships with pets Society & Animals: Social Scientific Studies of the Human Experience of Other Animals, vol. 4 (2), 121¿145.) and to reflect current theory of the consumer¿object relation. This research explores the potential of CSC through multi-site ethnography (Marcus, George E., (1995). Ethnography in/of the world system: the emergence of multi-sited ethnography, Annu Rev Anthropol 95¿117.) of a trans-national, highly-networked community of Afghan hounds and their exhibitors. The paper examines how companion species emerge across a range of cultural sites and documents the consumption practices stemming from the dichotomies between them. The conclusions inform dog-related marketing activity, advance consumer-research insights into the practices of dog-related avocational consumer groups, and extend existing theory of the consumer¿object relation.

Na área de emparelhamento de ontologias, são utilizadas algumas métricas para avaliar os alinhamentos produzidos. As métricas baseadas em alinhamento têm como princípio básico confrontar um alinhamento proposto com um alinhamento de referência. Algumas destas métricas, entretanto, não têm alcançado êxito suficiente porque (i) não conseguem discriminar sempre entre um alinhamento totalmente errado e um quase correto; e (ii) não conseguem estimar o esforço do usuário para refinar o alinhamento resultante. Este trabalho tem como objetivo apresentar uma nova abordagem para avaliar os alinhamentos de ontologias. A nossa abordagem apresenta uma métrica na qual utilizamos as próprias consultas normalmente já realizadas nas ontologias originais para julgar a qualidade do alinhamento proposto. Apresentamos também alguns resultados satisfatórios de nossa abordagem em relação às outras métricas já existentes e largamente utilizadas. / In the ontology matching field, different metrics are used to evaluate the resulting alignments. Metrics based on alignment adopt the basic principle of verifying a proposed alignment against a reference alignment. Some of these metrics do not achieve good results because (i) they cannot always distinguish between a totally wrong alignment and one which is almost correct; and (ii) they cannot estimate the effort for the user to refine the resulting alignment. This work aims to present a new approach to evaluate ontology alignments. Our approach presents a measure that uses the usual queries in the original ontologies to assess the quality of the proposed alignment. We also present some satisfactory results of our approach with regard to widely used metrics.

With the proliferation of electronic commerce and knowledge economy environments, both persons and organizations increasingly have generated and consumed large amounts of online information, typically available as textual documents. To manage this rapid growth of the number of textual documents, people often use categories or folders to organize their documents. These document grouping behaviors are intentional acts that reflect the persons¡¦ (or organizations¡¦) preferences with regard to semantic coherency, or relevant groupings between subjects. For this thesis, we design and implement an ontology-based personalized document clustering (OnPEC) technique by incorporating both an individual user¡¦s partial clustering and an ontology into the document clustering process. Our use of a target user¡¦s partial clustering supports the personalization of document categorization, whereas our use of the ontology turns document clustering from a feature-based to a concept-based approach. In addition, we combine two hierarchical agglomerative clustering (HAC) approaches (i.e., pre-cluster-based and atomic-based) in our proposed OnPEC technique. Using the clustering effectiveness achieved by a traditional content-based document clustering technique and previously proposed feature-based document clustering (PEC) techniques as performance benchmarks, we find that use of partial clusters improves document clustering effectiveness, as measured by cluster precision and cluster recall. Moreover, for both OnPEC and PEC techniques, the clustering effectiveness of pre-cluster-based HAC methods greatly outperforms that of atomic-based HAC methods.

<p>Though a constantly increasing number of ontologies are now available on the Internet, the ontology construction process remains generally a manual task, so consequently an effort demanding task. As no unified ontology construction method is available in the literature, researchers started investigating different frameworks for automatically generating ontologies and, therefore shorten the time required for their construction. This master’s thesis presents a prototype system for automatic construction of ontology, based on ontology design patterns and unstructured texts, such as natural language texts. The use of ontology design patterns allow constructing well structured ontologies and reducing the demand of knowledge experts. A difference between our prototype system and the systems presented in the literature is, the possibility to increase accuracy of the generated ontology by selecting the more relevant terms and associations from the unstructured text and match them against the ontology design patterns. Also, a matching score is introduced to define the level of similarity between the terms extracted and the ontology design patterns. By setting a threshold value on the matching score, the relevant ontology design patterns are selected and used for the ontology construction process. The ontology construction framework used by the prototype system has been developed by the research group in Information Engineering of the School of Engineering, Jönköping University.</p>

<p>Though a constantly increasing number of ontologies are now available on the Internet, the ontology construction process remains generally a manual task, so consequently an effort demanding task. As no unified ontology construction method is available in the literature, researchers started investigating different frameworks for automatically generating ontologies and, therefore shorten the time required for their construction. This master’s thesis presents a prototype system for automatic construction of ontology, based on ontology design patterns and unstructured texts, such as natural language texts. The use of ontology design patterns allow constructing well structured ontologies and reducing the demand of knowledge experts. A difference between our prototype system and the systems presented in the literature is, the possibility to increase accuracy of the generated ontology by selecting the more relevant terms and associations from the unstructured text and match them against the ontology design patterns. Also, a matching score is introduced to define the level of similarity between the terms extracted and the ontology design patterns. By setting a threshold value on the matching score, the relevant ontology design patterns are selected and used for the ontology construction process. The ontology construction framework used by the prototype system has been developed by the research group in Information Engineering of the School of Engineering, Jönköping University.</p> / <p>Även fast ett ökande antal ontologier är tillgängliga på Internet, är ontologikonstruktion fortfarande till största delen en manuell process, som därigenom kräver en stor arbetsinsats. Eftersom ingen enhetlig metodologi för att konstruera ontologier finns i litteraturen, forskare började undersöka olika ansatser för att automatiskt generera ontologier och därigenom förkorta konstruktionstiden. Detta examensarbete presenterar ett prototypsystem för automatisk konstruktion av ontologier, baserat på designmönster för ontologier och ostrukturerad text (text i naturligt språk). Att använda designmönster ger en välstrukturerad ontologi och minskar behovet av expertkunskap. En skillnad mellan vårt system och system i litteraturen är möjligheten att få en mer korrekt ontologi genom att välja de mestrelevanta termerna och relationerna från texterna och matcha dem motdesignmönstren. Ett värde för överensstämmelsen har införts för att kunna beskriva hur stor likhet som finns mellan termerna och designmönstren. Genom att sätta ett tröskelvärde väljs de relevanta designmönstren ut och används för att konstruera ontologin. Den generella processen för ontologikonstruktion som används av prototypsystemet har utvecklats av forskningsgruppen i Informationsteknik vid Ingenjörshögskolan i Jönköping.</p>

Knowledge-driven problem solving demands 'complete' knowledge about the domain and its interpretation under different contexts. Knowledge Morphing aims at a context-driven integration of heterogeneous knowledge sources--in order to provide a comprehensive and networked view of all knowledge about a domain-specific problem, pertaining to the context at hand. In this PhD thesis, we have proposed a Semantic Web based framework, K-MORPH, for Knowledge Morphing via Reconciliation of Contextualized Sub-ontologies. In order to realize our K-MORPH framework, we have developed: (i) a sub-ontology extraction method for generating contextualized sub-ontologies from the source ontologies pertinent to the problem-context at hand; (ii) two ontology matching approaches: triple-based ontology matching (TOM) and proof-based ontology matching (POM) for finding both atomic and complex correspondences between two extracted contextualized sub-ontologies; and (iii) our approach for resolving inconsistencies in ontologies by generating minimal inconsistent resolve candidates (MIRCs), where removing any of the MIRCs from the inconsistent ontology results in a maximal consistent sub-ontology. Thus, K-MORPH performs knowledge morphing among ontology-modelled knowledge sources and generates a context-sensitive and comprehensive knowledge-base pertinent to the problem at hand by (a) extracting problem-specific knowledge components from ontology-modelled knowledge sources using our sub-ontology extraction method; (b) aligning and merging the extracted knowledge components using our matching approaches; and (c) repairing inconsistencies in the morphed knowledge by applying our approach for detecting and resolving inconsistencies. We demonstrated the application of our K-MORPH framework in the healthcare domain, where K-MORPH generated a merged ontology for providing a comprehensive therapeutic knowledge-base for Urinary Tract Infections (UTI) by first (i) extracting 20 contextualized sub-ontologies from various UTI ontologies of different healthcare institutions, (ii) aligning and merging the extracted UTI sub-ontologies, and (iii) detecting and resolving inconsistencies in the merged UTI ontology.

The overall context of this thesis research is to explore natural language as a medium to interact with computer software in the graphics domain, e.g. programs like MS Paint or OpenGL. A core element of most natural language understanding systems is an ontology, which represents concepts and items of the underlying domain of discourse. This thesis presents an ontology for the graphics domain based on several resources, including documentation and textbooks on graphics systems, existing ontologies, and - most importantly - a collection of natural language instructions to create and modify graphic images. The ontology was developed in several phases, and finally tested as part of a complex natural language interface. This natural language interface accepts verbal instructions in the graphics domain as input and creates matching graphic images as output. The results of our tests indicate an accuracy of the system in the area of 80%.

The overall context of this thesis research is to explore natural language as a medium to interact with computer software in the graphics domain, e.g. programs like MS Paint or OpenGL. A core element of most natural language understanding systems is an ontology, which represents concepts and items of the underlying domain of discourse. This thesis presents an ontology for the graphics domain based on several resources, including documentation and textbooks on graphics systems, existing ontologies, and - most importantly - a collection of natural language instructions to create and modify graphic images. The ontology was developed in several phases, and finally tested as part of a complex natural language interface. This natural language interface accepts verbal instructions in the graphics domain as input and creates matching graphic images as output. The results of our tests indicate an accuracy of the system in the area of 80%.

There are two significant impedances to the realization of the potential of ontologies. First, many ontology designers lack the necessary background in formal logics to express their intuitions clearly and precisely, resulting in the proliferation of ontologies with low expressivity. Concurrently, developing semantic mappings between existing ontologies is difficult, because much of the semantics is external to the representation. This thesis uses the idea of metaphor to develop architectures for ontology repositories to serve as bottom-up reusable resources. Moreover, an ontology design algorithm has been developed that allows designers to communicate their ideas at the semantic level, simply by generating and vetting models. Finally, a semantic mapping algorithm has been developed that uses an ontology repository to determine the similarities and differences between any number of target ontologies. An ontology for partial orders has been elaborated to demonstrate the proof of concept and populate the first iteration of the repository.