985 resultados para work ontology
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This dissertation presents the first theoretical model for understanding narration and point of view in opera, examining repertoire from Richard Wagner to Benjamin Britten. Prior music scholarship on musical narratives and narrativity has drawn primarily on continental literary theory and philosophy of the 1960s to the middle of the 1980s. This study, by contrast, engages with current debates in the analytic branch of aesthetic philosophy. One reason why the concept of point of view has not been more extensively explored in opera studies is the widespread belief that operas are not narratives. This study questions key premises on which this assumption rests. In so doing, it presents a new definition of narrative. Arguably, a narrative is an utterance intended to communicate a story, where "story" is understood to involve the representation of a particular agent or agents exercising their agency. This study explores the role of narrators in opera, introducing the first taxonomy of explicit fictional operatic narrators. Through a close analysis of Britten and Myfanwy Piper's Owen Wingrave, it offers an explanation of music's power to orient spectators to the points of view of opera characters by providing audiences with access to characters' perceptual experiences and cognitive, affective, and psychological states. My analysis also helps account for how our subjective access to fictional characters may engender sympathy for them. The second half of the dissertation focuses on opera in performance. Current thinking in music scholarship predominantly holds that fidelity is an outmoded concern. I argue that performing a work-for-performance is a matter of intentionally modelling one's performance on the work-for-performance's features and achieving a moderate degree of fidelity or matching between the two. Finally, this study investigates how the creative decisions of the performers and director impact the point of view from which an opera is told.
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With the widespread applications of electronic learning (e-Learning) technologies to education at all levels, increasing number of online educational resources and messages are generated from the corresponding e-Learning environments. Nevertheless, it is quite difficult, if not totally impossible, for instructors to read through and analyze the online messages to predict the progress of their students on the fly. The main contribution of this paper is the illustration of a novel concept map generation mechanism which is underpinned by a fuzzy domain ontology extraction algorithm. The proposed mechanism can automatically construct concept maps based on the messages posted to online discussion forums. By browsing the concept maps, instructors can quickly identify the progress of their students and adjust the pedagogical sequence on the fly. Our initial experimental results reveal that the accuracy and the quality of the automatically generated concept maps are promising. Our research work opens the door to the development and application of intelligent software tools to enhance e-Learning.
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Over the last decade, the rapid growth and adoption of the World Wide Web has further exacerbated user needs for e±cient mechanisms for information and knowledge location, selection, and retrieval. How to gather useful and meaningful information from the Web becomes challenging to users. The capture of user information needs is key to delivering users' desired information, and user pro¯les can help to capture information needs. However, e®ectively acquiring user pro¯les is di±cult. It is argued that if user background knowledge can be speci¯ed by ontolo- gies, more accurate user pro¯les can be acquired and thus information needs can be captured e®ectively. Web users implicitly possess concept models that are obtained from their experience and education, and use the concept models in information gathering. Prior to this work, much research has attempted to use ontologies to specify user background knowledge and user concept models. However, these works have a drawback in that they cannot move beyond the subsumption of super - and sub-class structure to emphasising the speci¯c se- mantic relations in a single computational model. This has also been a challenge for years in the knowledge engineering community. Thus, using ontologies to represent user concept models and to acquire user pro¯les remains an unsolved problem in personalised Web information gathering and knowledge engineering. In this thesis, an ontology learning and mining model is proposed to acquire user pro¯les for personalised Web information gathering. The proposed compu- tational model emphasises the speci¯c is-a and part-of semantic relations in one computational model. The world knowledge and users' Local Instance Reposito- ries are used to attempt to discover and specify user background knowledge. From a world knowledge base, personalised ontologies are constructed by adopting au- tomatic or semi-automatic techniques to extract user interest concepts, focusing on user information needs. A multidimensional ontology mining method, Speci- ¯city and Exhaustivity, is also introduced in this thesis for analysing the user background knowledge discovered and speci¯ed in user personalised ontologies. The ontology learning and mining model is evaluated by comparing with human- based and state-of-the-art computational models in experiments, using a large, standard data set. The experimental results are promising for evaluation. The proposed ontology learning and mining model in this thesis helps to develop a better understanding of user pro¯le acquisition, thus providing better design of personalised Web information gathering systems. The contributions are increasingly signi¯cant, given both the rapid explosion of Web information in recent years and today's accessibility to the Internet and the full text world.
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Intelligent agents are an advanced technology utilized in Web Intelligence. When searching information from a distributed Web environment, information is retrieved by multi-agents on the client site and fused on the broker site. The current information fusion techniques rely on cooperation of agents to provide statistics. Such techniques are computationally expensive and unrealistic in the real world. In this paper, we introduce a model that uses a world ontology constructed from the Dewey Decimal Classification to acquire user profiles. By search using specific and exhaustive user profiles, information fusion techniques no longer rely on the statistics provided by agents. The model has been successfully evaluated using the large INEX data set simulating the distributed Web environment.
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Recently, user tagging systems have grown in popularity on the web. The tagging process is quite simple for ordinary users, which contributes to its popularity. However, free vocabulary has lack of standardization and semantic ambiguity. It is possible to capture the semantics from user tagging into some form of ontology, but the application of the resulted ontology for recommendation making has not been that flourishing. In this paper we discuss our approach to learn domain ontology from user tagging information and apply the extracted tag ontology in a pilot tag recommendation experiment. The initial result shows that by using the tag ontology to re-rank the recommended tags, the accuracy of the tag recommendation can be improved.
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Different reputation models are used in the web in order to generate reputation values for products using uses' review data. Most of the current reputation models use review ratings and neglect users' textual reviews, because it is more difficult to process. However, we argue that the overall reputation score for an item does not reflect the actual reputation for all of its features. And that's why the use of users' textual reviews is necessary. In our work we introduce a new reputation model that defines a new aggregation method for users' extracted opinions about products' features from users' text. Our model uses features ontology in order to define general features and sub-features of a product. It also reflects the frequencies of positive and negative opinions. We provide a case study to show how our results compare with other reputation models.
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Objective To develop and evaluate machine learning techniques that identify limb fractures and other abnormalities (e.g. dislocations) from radiology reports. Materials and Methods 99 free-text reports of limb radiology examinations were acquired from an Australian public hospital. Two clinicians were employed to identify fractures and abnormalities from the reports; a third senior clinician resolved disagreements. These assessors found that, of the 99 reports, 48 referred to fractures or abnormalities of limb structures. Automated methods were then used to extract features from these reports that could be useful for their automatic classification. The Naive Bayes classification algorithm and two implementations of the support vector machine algorithm were formally evaluated using cross-fold validation over the 99 reports. Result Results show that the Naive Bayes classifier accurately identifies fractures and other abnormalities from the radiology reports. These results were achieved when extracting stemmed token bigram and negation features, as well as using these features in combination with SNOMED CT concepts related to abnormalities and disorders. The latter feature has not been used in previous works that attempted classifying free-text radiology reports. Discussion Automated classification methods have proven effective at identifying fractures and other abnormalities from radiology reports (F-Measure up to 92.31%). Key to the success of these techniques are features such as stemmed token bigrams, negations, and SNOMED CT concepts associated with morphologic abnormalities and disorders. Conclusion This investigation shows early promising results and future work will further validate and strengthen the proposed approaches.
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More and more traditional manufacturing companies form or join inter-organizational networks to bundle their physical products with related services to offer superior value propositions to their customers. Some of these product-related services can be digitized completely and thus fully delivered electronically. Other services require the physical integration of external factors, but can still be coordinated electronically. In both cases companies and consumers face the problem of discovering appropriate product-related service offerings in the network or market. Based on ideas from the web service discovery discipline we propose a meet-in-the-middle approach between heavy-weight semantic technologies and simple boolean search to address this issue. Our approach is able to consider semantic relations in service descriptions and queries and thus delivers better results than syntax-based search. However – unlike most semantic approaches – it does not require the use of any formal language for semantic markup and thus requires less resources and skills for both service providers and consumers. To fully realize the potentials of the proposed approach a domain ontology is needed. In this research-in-progress paper we construct such an ontology for the domain of product-service bundles through analysis and synthesis of related work on service description. This will serve as an anchor for future research to iteratively improve and evaluate the ontology through collaborative design efforts and practical application.
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Differences in gene expression of human bone marrow stromal cells (hBMSCs) during culture in three-dimensional (3D) nanofiber scaffolds or on two-dimensional (2D) films were investigated via pathway analysis of microarray mRNA expression profiles. Previous work has shown that hBMSC culture in nanofiber scaffolds can induce osteogenic differentiation in the absence of osteogenic supplements (OS). Analysis using ontology databases revealed that nanofibers and OS regulated similar pathways and that both were enriched for TGF-beta and cell-adhesion/ECM-receptor pathways. The most notable difference between the two was that nanofibers had stronger enrichment for cell-adhesion/ECM-receptor pathways. Comparison of nanofibers scaffolds with flat films yielded stronger differences in gene expression than comparison of nanofibers made from different polymers, suggesting that substrate structure had stronger effects on cell function than substrate polymer composition. These results demonstrate that physical (nanofibers) and biochemical (OS) signals regulate similar ontological pathways, suggesting that these cues use similar molecular mechanisms to control hBMSC differentiation. Published by Elsevier Ltd.
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A modelagem orientada a agentes surge como paradigma no desenvolvimento de software, haja vista a quantidade de iniciativas e estudos que remetem à utilização de agentes de software como solução para tratar de problemas mais complexos. Apesar da popularidade de utilização de agentes, especialistas esbarram na falta de universalidade de uma metodologia para construção dos Sistemas Multiagentes (MAS), pois estas acabam pecando pelo excesso ou falta de soluções para modelar o problema. Esta dissertação propõe o uso de uma Ontologia sobre Metodologias Multiagentes, seguindo os princípios da Engenharia de Métodos Situacionais que se propõe a usar fragmentos de métodos para construção de metodologias baseados na especificidade do projeto em desenvolvimento. O objetivo do estudo é sedimentar o conhecimento na área de Metodologias Multiagentes, auxiliando o engenheiro de software a escolher a melhor metodologia ou o melhor fragmento de metodologia capaz de modelar um Sistema Multiagentes.
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© 2014, Springer-Verlag London. Engineering changes are essential for any product development, and their management has become a crucial discipline. Research in engineering change management has brought about some methods and tools to support dealing with changes. This work extends the change prediction method through incorporation of a function–behaviour–structure (FBS) scheme. These additional levels of detail provide the rationales for change propagation and allow a more proactive management of changes. First, we develop the ontology of this method based on a comprehensive comparison of three seminal functional reasoning schemes. Then, we demonstrate the FBS Linkage technique by applying it to a diesel engine. Finally, we evaluate the method.
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Purpose and rationale The purpose of the exploratory research is to provide a deeper understanding of how the work environment enhances or constrains organisational creativity (creativity and innovation) within the context of the advertising sector. The argument for the proposed research is that the contemporary literature is dominated by quantitative research instruments to measure the climate and work environment across many different sectors. The most influential theory within the extant literature is the componential theory of organisational creativity and innovation and is used as an analytical guide (Amabile, 1997; Figure 8) to conduct an ethnographic study within a creative advertising agency based in Scotland. The theory suggests that creative people (skills, expertise and task motivation) are influenced by the work environment in which they operate. This includes challenging work (+), work group supports (+), supervisory encouragement (+), freedom (+), sufficient resources (+), workload pressures (+ or -), organisational encouragement (+) and organisational impediments (-) which is argued enhances (+) or constrains (-) both creativity and innovation. An interpretive research design is conducted to confirm, challenge or extend the componential theory of organisational creativity and innovation (Amabile, 1997; Figure 8) and contribute to knowledge as well as practice. Design/methodology/approach The scholarly activity conducted within the context of the creative industries and advertising sector is in its infancy and research from the alternative paradigm using qualitative methods is limited which may provide new guidelines for this industry sector. As such, an ethnographic case study research design is a suitable methodology to provide a deeper understanding of the subject area and is consistent with a constructivist ontology and an interpretive epistemology. This ontological position is conducive to the researcher’s axiology and values in that meaning is not discovered as an objective truth but socially constructed from multiple realties from social actors. As such, ethnography is the study of people in naturally occurring settings and the creative advertising agency involved in the research is an appropriate purposive sample within an industry that is renowned for its creativity and innovation. Qualitative methods such as participant observation (field notes, meetings, rituals, social events and tracking a client brief), material artefacts (documents, websites, annual reports, emails, scrapbooks and photographic evidence) and focused interviews (informal and formal conversations, six taped and transcribed interviews and use of Survey Monkey) are used to provide a written account of the agency’s work environment. The analytical process of interpreting the ethnographic text is supported by thematic analysis (selective, axial and open coding) through the use of manual analysis and NVivo9 software Findings The findings highlight a complex interaction between the people within the agency and the enhancers and constraints of the work environment in which they operate. This involves the creative work environment (Amabile, 1997; Figure 8) as well as the physical work environment (Cain, 2012; Dul and Ceylan, 2011; Dul et al. 2011) and that of social control and power (Foucault, 1977; Gahan et al. 2007; Knights and Willmott, 2007). As such, the overarching themes to emerge from the data on how the work environment enhances or constrains organisational creativity include creative people (skills, expertise and task motivation), creative process (creative work environment and physical work environment) and creative power (working hours, value of creativity, self-fulfilment and surveillance). Therefore, the findings confirm that creative people interact and are influenced by aspects of the creative work environment outlined by Amabile (1997; Figure 8). However, the results also challenge and extend the theory to include that of the physical work environment and creative power. Originality/value/implications Methodologically, there is no other interpretive research that uses an ethnographic case study approach within the context of the advertising sector to explore and provide a deeper understanding of the subject area. As such, the contribution to knowledge in the form of a new interpretive framework (Figure 16) challenges and extends the existing body of knowledge (Amabile, 1997; Figure 8). Moreover, the contribution to practice includes a flexible set of industry guidelines (Appendix 13) that may be transferrable to other organisational settings.
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To be presented at SIG/ISMB07 ontology workshop: http://bio-ontologies.org.uk/index.php To be published in BMC Bioinformatics. Sponsorship: JISC
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The task of this work is to apply thoughts from Georg Lukács’ final book, the Ontology of Social Being, for the theoretical analysis of cultural and digital labour. It discusses Lukács’ concepts of work and communication and relates them to the analysis of cultural and digital work. It also analyses his conception of the relation of labour and ideology and points out how we can make use of it for critically understanding social media ideologies. Lukács opposes the dualist separation of the realms of work and ideas. He introduces in this context the notion of teleological positing that allows us to better understand cultural and digital labour as well as associated ideologies, such as the engaging/connecting/sharing-ideology, today. The analysis shows that Lukács’ Ontology is in the age of Facebook, YouTube, and Twitter still a very relevant book, although it has thus far not received the attention that it deserves. This article also introduces the Ontology’s main ideas on work and culture, which is important because large parts of the book have not been translated from the German original into English. Lukács’ notion of teleological positing is crucial for understanding the common features of the economy and culture.
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Os Mercados Eletrónicos atingiram uma complexidade e nível de sofisticação tão elevados, que tornaram inadequados os modelos de software convencionais. Estes mercados são caracterizados por serem abertos, dinâmicos e competitivos, e constituídos por várias entidades independentes e heterogéneas. Tais entidades desempenham os seus papéis de forma autónoma, seguindo os seus objetivos, reagindo às ocorrências do ambiente em que se inserem e interagindo umas com as outras. Esta realidade levou a que existisse por parte da comunidade científica um especial interesse no estudo da negociação automática executada por agentes de software [Zhang et al., 2011]. No entanto, a diversidade dos atores envolvidos pode levar à existência de diferentes conceptualizações das suas necessidades e capacidades dando origem a incompatibilidades semânticas, que podem prejudicar a negociação e impedir a ocorrência de transações que satisfaçam as partes envolvidas. Os novos mercados devem, assim, possuir mecanismos que lhes permitam exibir novas capacidades, nomeadamente a capacidade de auxiliar na comunicação entre os diferentes agentes. Pelo que, é defendido neste trabalho que os mercados devem oferecer serviços de ontologias que permitam facilitar a interoperabilidade entre os agentes. No entanto, os humanos tendem a ser relutantes em aceitar a conceptualização de outros, a não ser que sejam convencidos de que poderão conseguir um bom negócio. Neste contexto, a aplicação e exploração de relações capturadas em redes sociais pode resultar no estabelecimento de relações de confiança entre vendedores e consumidores, e ao mesmo tempo, conduzir a um aumento da eficiência da negociação e consequentemente na satisfação das partes envolvidas. O sistema AEMOS é uma plataforma de comércio eletrónico baseada em agentes que inclui serviços de ontologias, mais especificamente, serviços de alinhamento de ontologias, incluindo a recomendação de possíveis alinhamentos entre as ontologias dos parceiros de negociação. Este sistema inclui também uma componente baseada numa rede social, que é construída aplicando técnicas de análise de redes socias sobre informação recolhida pelo mercado, e que permite melhorar a recomendação de alinhamentos e auxiliar os agentes na sua escolha. Neste trabalho são apresentados o desenvolvimento e implementação do sistema AEMOS, mais concretamente: • É proposto um novo modelo para comércio eletrónico baseado em agentes que disponibiliza serviços de ontologias; • Adicionalmente propõem-se o uso de redes sociais emergentes para captar e explorar informação sobre relações entre os diferentes parceiros de negócio; • É definida e implementada uma componente de serviços de ontologias que é capaz de: • o Sugerir alinhamentos entre ontologias para pares de agentes; • o Traduzir mensagens escritas de acordo com uma ontologia em mensagens escritas de acordo com outra, utilizando alinhamentos previamente aprovados; • o Melhorar os seus próprios serviços recorrendo às funcionalidades disponibilizadas pela componente de redes sociais; • É definida e implementada uma componente de redes sociais que: • o É capaz de construir e gerir um grafo de relações de proximidade entre agentes, e de relações de adequação de alinhamentos a agentes, tendo em conta os perfis, comportamento e interação dos agentes, bem como a cobertura e utilização dos alinhamentos; • o Explora e adapta técnicas e algoritmos de análise de redes sociais às várias fases dos processos do mercado eletrónico. A implementação e experimentação do modelo proposto demonstra como a colaboração entre os diferentes agentes pode ser vantajosa na melhoria do desempenho do sistema e como a inclusão e combinação de serviços de ontologias e redes sociais se reflete na eficiência da negociação de transações e na dinâmica do mercado como um todo.