983 resultados para Domain Ontology


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Background: The failure rate of health information systems is high, partially due to fragmented, incomplete, or incorrect identification and description of specific and critical domain requirements. In order to systematically transform the requirements of work into real information system, an explicit conceptual framework is essential to summarize the work requirements and guide system design. Recently, Butler, Zhang, and colleagues proposed a conceptual framework called Work Domain Ontology (WDO) to formally represent users’ work. This WDO approach has been successfully demonstrated in a real world design project on aircraft scheduling. However, as a top level conceptual framework, this WDO has not defined an explicit and well specified schema (WDOS) , and it does not have a generalizable and operationalized procedure that can be easily applied to develop WDO. Moreover, WDO has not been developed for any concrete healthcare domain. These limitations hinder the utility of WDO in real world information system in general and in health information system in particular. Objective: The objective of this research is to formalize the WDOS, operationalize a procedure to develop WDO, and evaluate WDO approach using Self-Nutrition Management (SNM) work domain. Method: Concept analysis was implemented to formalize WDOS. Focus group interview was conducted to capture concepts in SNM work domain. Ontology engineering methods were adopted to model SNM WDO. Part of the concepts under the primary goal “staying healthy” for SNM were selected and transformed into a semi-structured survey to evaluate the acceptance, explicitness, completeness, consistency, experience dependency of SNM WDO. Result: Four concepts, “goal, operation, object and constraint”, were identified and formally modeled in WDOS with definitions and attributes. 72 SNM WDO concepts under primary goal were selected and transformed into semi-structured survey questions. The evaluation indicated that the major concepts of SNM WDO were accepted by 41 overweight subjects. SNM WDO is generally independent of user domain experience but partially dependent on SNM application experience. 23 of 41 paired concepts had significant correlations. Two concepts were identified as ambiguous concepts. 8 extra concepts were recommended towards the completeness of SNM WDO. Conclusion: The preliminary WDOS is ready with an operationalized procedure. SNM WDO has been developed to guide future SNM application design. This research is an essential step towards Work-Centered Design (WCD).

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This chapter presents methodological guidelines that allow engineers to reuse generic ontologies. This kind of ontologies represents notions generic across many fields, (is part of, temporal interval, etc.). The guidelines helps the developer (a) to identify the type of generic ontology to be reused, (b) to find out the axioms and definitions that should be reused and (c) to adapt and integrate the generic ontology selected in the domain ontology to be developed. For each task of the methodology, a set of heuristics with examples are presented. We hope that after reading this chapter, you would have acquired some basic ideas on how to take advantage of the great deal of well-founded explicit knowledge that formalizes generic notions such as time concepts and the part of relation.

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The main idea of our approach is that the domain ontology is not only the instrument of learning but an object of examining student skills. We propose for students to build the domain ontology of examine discipline and then compare it with etalon one. Analysis of student mistakes allows to propose them personalized recommendations and to improve the course materials in general. For knowledge interoperability we apply Semantic Web technologies. Application of agent-based technologies in e-learning provides the personification of students and tutors and saved all users from the routine operations.

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* This paper was made according to the program No 14 of fundamental scientific research of the Presidium of the Russian Academy of Sciences, the project "Intellectual Systems Based on Multilevel Domain Models".

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* This paper was made according to the program of fundamental scientific research of the Presidium of the Russian Academy of Sciences «Mathematical simulation and intellectual systems», the project "Theoretical foundation of the intellectual systems based on ontologies for intellectual support of scientific researches".

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* This paper was made according to the program of fundamental scientific research of the Presidium of the Russian Academy of Sciences «Mathematical simulation and intellectual systems», the project "Theoretical foundation of the intellectual systems based on ontologies for intellectual support of scientific researches".

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As of today, online reviews have become more and more important in decision making process. In recent years, the problem of identifying useful reviews for users has attracted significant attentions. For instance, in order to select reviews that focus on a particular feature, researchers proposed a method which extracts all associated words of this feature as the relevant information to evaluate and find appropriate reviews. However, the extraction of associated words is not that accurate due to the noise in free review text, and this affects the overall performance negatively. In this paper, we propose a method to select reviews according to a given feature by using a review model generated based upon a domain ontology called product feature taxonomy. The proposed review model provides relevant information about the hierarchical relationships of the features in the review which captures the review characteristics accurately. Our experiment results based on real world review dataset show that our approach is able to improve the review selection performance according to the given criteria effectively.

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As of today, user-generated information such as online reviews has become increasingly significant for customers in decision making process. Meanwhile, as the volume of online reviews proliferates, there is an insistent demand to help the users tackle the information overload problem. In order to extract useful information from overwhelming reviews, considerable work has been proposed such as review summarization and review selection. Particularly, to avoid the redundant information, researchers attempt to select a small set of reviews to represent the entire review corpus by preserving its statistical properties (e.g., opinion distribution). However, one significant drawback of the existing works is that they only measure the utility of the extracted reviews as a whole without considering the quality of each individual review. As a result, the set of chosen reviews may consist of low-quality ones even its statistical property is close to that of the original review corpus, which is not preferred by the users. In this paper, we proposed a review selection method which takes review quality into consideration during the selection process. Specifically, we examine the relationships between product features based upon a domain ontology to capture the review characteristics based on which to select reviews that have good quality and preserve the opinion distribution as well. Our experimental results based on real world review datasets demonstrate that our proposed approach is feasible and able to improve the performance of the review selection effectively.

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O problema que justifica o presente estudo refere-se à falta de semântica nos mecanismos de busca na Web. Para este problema, o consórcio W3 vem desenvolvendo tecnologias que visam construir uma Web Semântica. Entre estas tecnologias, estão as ontologias de domínio. Neste sentido, o objetivo geral desta dissertação é discutir as possibilidades de se imprimir semântica às buscas nos agregadores de notícia da Web. O objetivo específico é apresentar uma aplicação que usa uma classificação semi-automática de notícias, reunindo, para tanto, as tecnologias de busca da área de recuperação de informação com as ontologias de domínio. O sistema proposto é uma aplicação para a Web capaz de buscar notícias sobre um domínio específico em portais de informação. Ela utiliza a API do Google Maps V1 para a localização georreferenciada da notícia, sempre que esta informação estiver disponível. Para mostrar a viabilidade da proposta, foi desenvolvido um exemplo apoiado em uma ontologia para o domínio de chuvas e suas consequências. Os resultados obtidos por este novo Feed de base ontológica são alocados em um banco de dados e disponibilizados para consulta via Web. A expectativa é que o Feed proposto seja mais relevante em seus resultados do que um Feed comum. Os resultados obtidos com a união de tecnologias patrocinadas pelo consórcio W3 (XML, RSS e ontologia) e ferramentas de busca em página Web foram satisfatórios para o propósito pretendido. As ontologias mostram-se como ferramentas de usos múltiplos, e seu valor de análise em buscas na Web pode ser ampliado com aplicações computacionais adequadas para cada caso. Como no exemplo apresentado nesta dissertação, à palavra chuva agregaram-se outros conceitos, que estavam presentes nos desdobramentos ocasionados por ela. Isto realçou a ligação do evento chuva com as consequências que ela provoca - ação que só foi possível executar através de um recorte do conhecimento formal envolvido.

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政府信息检索系统作为政府信息公开平台的重要组成部分,对于用户从大量信息中准确查找所需信息起到关键作用,然而现有政府信息检索系统存在两个主要问题:一是系统采用的基于关键词匹配的检索技术忽视了对于用户检索条件的语义的理解,缺乏对于文档实质内涵的准确描述;二是由于对政府信息领域知识的缺乏,用户不能很好地提出符合自己检索需求的检索条件。这两个问题导致检索结果远远不能满足用户的要求。 本体是“概念模型的明确的规范说明”,它提供明确定义的词汇表,描述概念和概念之间的关系,被当作某个领域内不同主体之间进行交流的一种语义基础。它被广泛的应用于信息检索,特别是基于知识的检索中,能显著提高检索系统的查全率和查准率。 本文提出了构建政府信息领域本体并将其应用于政府信息检索系统的方案。首先,研究了现有的领域本体构建方法;在分析了政府信息领域的特点,考察了该领域可用资源的基础上,提出了基于政务主题词表的政府信息领域本体的构建方法。该方法充分利用了《综合电子政务主题词表》中已有的主题词和关系,保证了本体概念添加的完备性和科学性,减少了对领域专家的依赖,提高了构建效率。 设计和实现了基于领域本体的政府信息检索系统。该系统以领域本体为核心,对检索条件进行了扩展,既解决了检索词同政府信息中的公文用词存在差异的问题,又进一步明确了用户的检索需求;对政府信息文档进行了语义标注,提高了检索匹配时的准确度。同时,系统将与检索条件相关的领域概念反馈给用户,便于用户了解领域知识,进一步优化检索条件,获得更全更准的检索结果。

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为了构建政府信息领域本体,将其应用于政府信息检索系统中,提高系统的查全率和查准率,提出了利用现有术语丰富的政务主题词表构建政府信息领域本体的方法。该方法以政府信息这个核心概念和其属性为中心,将政务主题词表中的主题词和词间关系有序的转化到本体中,并在此基础上进一步挖掘了领域业务相关的关系,丰富了本体蕴涵的知识。进而将本体应用于政府信息检索系统中,改善了原系统的检索效果,同时也验证了该本体构建方法的有效性。

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Context awareness, dynamic reconfiguration at runtime and heterogeneity are key characteristics of future distributed systems, particularly in ubiquitous and mobile computing scenarios. The main contributions of this dissertation are theoretical as well as architectural concepts facilitating information exchange and fusion in heterogeneous and dynamic distributed environments. Our main focus is on bridging the heterogeneity issues and, at the same time, considering uncertain, imprecise and unreliable sensor information in information fusion and reasoning approaches. A domain ontology is used to establish a common vocabulary for the exchanged information. We thereby explicitly support different representations for the same kind of information and provide Inter-Representation Operations that convert between them. Special account is taken of the conversion of associated meta-data that express uncertainty and impreciseness. The Unscented Transformation, for example, is applied to propagate Gaussian normal distributions across highly non-linear Inter-Representation Operations. Uncertain sensor information is fused using the Dempster-Shafer Theory of Evidence as it allows explicit modelling of partial and complete ignorance. We also show how to incorporate the Dempster-Shafer Theory of Evidence into probabilistic reasoning schemes such as Hidden Markov Models in order to be able to consider the uncertainty of sensor information when deriving high-level information from low-level data. For all these concepts we provide architectural support as a guideline for developers of innovative information exchange and fusion infrastructures that are particularly targeted at heterogeneous dynamic environments. Two case studies serve as proof of concept. The first case study focuses on heterogeneous autonomous robots that have to spontaneously form a cooperative team in order to achieve a common goal. The second case study is concerned with an approach for user activity recognition which serves as baseline for a context-aware adaptive application. Both case studies demonstrate the viability and strengths of the proposed solution and emphasize that the Dempster-Shafer Theory of Evidence should be preferred to pure probability theory in applications involving non-linear Inter-Representation Operations.

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Web services are becoming popular and widely accepted on the Internet. UDDI is the standard for publishing and discovery of web services. In this paper, we investigate semantics description of web services based on domain ontology; based on this language, we propose an architecture for invoking agents to consume services within the UDDI registry. The semantics service description language together with agent creation
architecture provides a new way to discover and utilise published web services. This method is flexible and extendable to accomplish complex web service requests.

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Business process (BP) modeling aims at a better understanding of processes, allowing deciders to improve them. We propose to support this modeling with an approach encompassing methods and tools for BP models quality measurement and improvement. In this paper we focus on semantic quality. The latter is evaluated by aligning BP model concepts with domain knowledge. The alignment is conducted thanks to meta-models. We also define validation rules for checking the completeness of BP models. A medical case study illustrates the main steps of our approach.