820 resultados para religious discovery


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This paper describes the evaluation in benchmarking the effectiveness of cross-lingual link discovery (CLLD). Cross lingual link discovery is a way of automatically finding prospective links between documents in different languages, which is particularly helpful for knowledge discovery of different language domains. A CLLD evaluation framework is proposed for system performance benchmarking. The framework includes standard document collections, evaluation metrics, and link assessment and evaluation tools. The evaluation methods described in this paper have been utilised to quantify the system performance at NTCIR-9 Crosslink task. It is shown that using the manual assessment for generating gold standard can deliver a more reliable evaluation result.

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This paper demonstrates an experimental study that examines the accuracy of various information retrieval techniques for Web service discovery. The main goal of this research is to evaluate algorithms for semantic web service discovery. The evaluation is comprehensively benchmarked using more than 1,700 real-world WSDL documents from INEX 2010 Web Service Discovery Track dataset. For automatic search, we successfully use Latent Semantic Analysis and BM25 to perform Web service discovery. Moreover, we provide linking analysis which automatically links possible atomic Web services to meet the complex requirements of users. Our fusion engine recommends a final result to users. Our experiments show that linking analysis can improve the overall performance of Web service discovery. We also find that keyword-based search can quickly return results but it has limitation of understanding users’ goals.

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Spirituality and religiosity have traditionally had a troubled relationship with psychology. However, a new field of study has emerged that is examining the health benefits of spirituality and religion. The current study examined the relationship between spirituality, religiosity and coping among a group of university students facing exams. Participants completed the Spiritual Well-Being Scale, Age Universal Religious Orientation Scale, Spiritual Transcendence Scale, Brief COPE, Test Anxiety Inventory, and State Trait Anxiety Inventory. Regression analyses found that existential well-being as measured by the Spiritual Well Being Scale was the best predictor of reduced anxiety. Maladaptive coping, however, was found to be inversely related to spirituality and religiosity, but highly predictive of elevated anxiety in this sample. Strengths and limitations of this study along with recommendations for further research are made.

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This research explores the function of entrepreneurship in nonprofit art museums. Traditionally, entrepreneurship literature features debates on customer orientation and innovation. This paper reviews a tension in entrepreneurship: the relationship between limited funding and the need to innovate in nonprofit art museums. The paper develops a construct by which to explain the structure of entrepreneurship in nonprofit art museums in Australia and New Zealand since 1975. From this discussion, different strategies and tensions are highlighted that nonprofit art museum directors have used. The dynamics are explored in ten large art museums and the managerial implications are developed.

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Electronic services are a leitmotif in ‘hot’ topics like Software as a Service, Service Oriented Architecture (SOA), Service oriented Computing, Cloud Computing, application markets and smart devices. We propose to consider these in what has been termed the Service Ecosystem (SES). The SES encompasses all levels of electronic services and their interaction, with human consumption and initiation on its periphery in much the same way the ‘Web’ describes a plethora of technologies that eventuate to connect information and expose it to humans. Presently, the SES is heterogeneous, fragmented and confined to semi-closed systems. A key issue hampering the emergence of an integrated SES is Service Discovery (SD). A SES will be dynamic with areas of structured and unstructured information within which service providers and ‘lay’ human consumers interact; until now the two are disjointed, e.g., SOA-enabled organisations, industries and domains are choreographed by domain experts or ‘hard-wired’ to smart device application markets and web applications. In a SES, services are accessible, comparable and exchangeable to human consumers closing the gap to the providers. This requires a new SD with which humans can discover services transparently and effectively without special knowledge or training. We propose two modes of discovery, directed search following an agenda and explorative search, which speculatively expands knowledge of an area of interest by means of categories. Inspired by conceptual space theory from cognitive science, we propose to implement the modes of discovery using concepts to map a lay consumer’s service need to terminologically sophisticated descriptions of services. To this end, we reframe SD as an information retrieval task on the information attached to services, such as, descriptions, reviews, documentation and web sites - the Service Information Shadow. The Semantic Space model transforms the shadow's unstructured semantic information into a geometric, concept-like representation. We introduce an improved and extended Semantic Space including categorization calling it the Semantic Service Discovery model. We evaluate our model with a highly relevant, service related corpus simulating a Service Information Shadow including manually constructed complex service agendas, as well as manual groupings of services. We compare our model against state-of-the-art information retrieval systems and clustering algorithms. By means of an extensive series of empirical evaluations, we establish optimal parameter settings for the semantic space model. The evaluations demonstrate the model’s effectiveness for SD in terms of retrieval precision over state-of-the-art information retrieval models (directed search) and the meaningful, automatic categorization of service related information, which shows potential to form the basis of a useful, cognitively motivated map of the SES for exploratory search.

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This paper reports an exploration of religious information literacy in terms of how people use information to learn in the context of church communities. The research approach of phenomenography was used to explore Uniting Church in Australia members' experience of using information to learn as participants in their church communities. Five ways of experiencing religious information literacy were identified, using information to learn about: growing faith, developing relationships, managing the church, serving church communities and reaching out beyond church communities. It is anticipated that such findings will be of interest to information professionals, including information literacy specialists, as well as leaders and members of church communities.

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This thesis is an ethical and empirical exploration of the late discovery of genetic origins in two contexts, adoption and sperm donor-assisted conception. This exploration has two interlinked strands of concern. The first is the identification of ‘late discovery’ as a significant issue of concern, deserving of recognition and acknowledgment. The second concerns the ethical implications of late discovery experiences for the welfare of the child. The apparently simple act of recognition of a phenomenon is a precondition to any analysis and critique of it. This is especially important when the phenomenon arises out of social practices that arouse significant debate in ethical and legal contexts. As the new reproductive technologies and some adoption practices remain highly contested, an ethical exploration of this long neglected experience has the potential to offer new insights and perspectives in a range of contexts. It provides an opportunity to revisit developmental debate on the relative merit or otherwise of biological versus social influences, from the perspective of those who have lived this dichotomy in practise. Their experiences are the human face of the effects arising from decisions taken by others to intentionally separate their biological and social worlds, an action which has then been compounded by family and institutional secrecy from birth. This has been accompanied by a failure to ensure that normative standards and values are upheld for them. Following discovery, these factors can be exacerbated by a lack of recognition and acknowledgement of their concerns by family, friends, community and institutions. Late discovery experiences offer valuable insights to inform discussions on the ethical meanings of child welfare, best interests, parental responsibility, duty of care and child identity rights in this and other contexts. They can strengthen understandings of what factors are necessary for a child to be able to live a reasonably happy or worthwhile life.

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This paper addresses the issue of analogical inference, and its potential role as the mediator of new therapeutic discoveries, by using disjunction operators based on quantum connectives to combine many potential reasoning pathways into a single search expression. In it, we extend our previous work in which we developed an approach to analogical retrieval using the Predication-based Semantic Indexing (PSI) model, which encodes both concepts and the relationships between them in high-dimensional vector space. As in our previous work, we leverage the ability of PSI to infer predicate pathways connecting two example concepts, in this case comprising of known therapeutic relationships. For example, given that drug x TREATS disease z, we might infer the predicate pathway drug x INTERACTS WITH gene y ASSOCIATED WITH disease z, and use this pathway to search for drugs related to another disease in similar ways. As biological systems tend to be characterized by networks of relationships, we evaluate the ability of quantum-inspired operators to mediate inference and retrieval across multiple relations, by testing the ability of different approaches to recover known therapeutic relationships. In addition, we introduce a novel complex vector based implementation of PSI, based on Plate’s Circular Holographic Reduced Representations, which we utilize for all experiments in addition to the binary vector based approach we have applied in our previous research.

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A qualitative, discourse analytic study of literate practices in a small religious community in a northern Australian city. The chapter documents how this community constructs religious reading and writing, affiliated ideologies and theologies, and how readers/hearers/learners are positions vis a vis the authority of sacred text.

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Late discovery is a term used to describe the experience of discovering the truth of one’s genetic origins as an adult. Following discovery, late discoverers face a lack of recognition and acknowledgment of their concerns from family, friends, community and institutions. They experience pain, anger, loss, grief and frustration. This presentation shares the findings of the first qualitative study of both late discovery of adoptive and donor insemination offspring (heterosexual couple use only) experiences. It is also the first study of late discovery experiences undertaken from an ethical perspective. While this study recruited new participants, it also included an ethical re-analysis of existing late discovery accounts across both practices. The findings of this study (a) draws links between past adoption and current donor insemination (heterosexual couple only) practices, (b) reveals that late discoverers are demanding acknowledgment and recognition of the particularity of their experiences, and (c) offers insights into conceptual understandings of the ‘best interests of the child’ principle. These insights derive from the lived experiences of those whose biological and social worlds have been sundered and secrecy and denial of difference used to conceal this. It suggests that acknowledging the equal moral status of the child may be useful in strengthening conceptual understandings of the ‘best interests of the child’ principle. This equal moral status involves ensuring that personal autonomy and the ability to exercise free will is protected; that the integrity of the relationships of trust expected and demanded between parent/s and children is defended and supported; and that equal access to normative socio-cultural practices, that is; non-fictionalised birth certificates and open records, is guaranteed.

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In this paper we examine automated Chinese to English link discovery in Wikipedia and the effects of Chinese segmentation and Chinese to English translation on the hyperlink recommendation. Our experimental results show that the implemented link discovery framework can effectively recommend Chinese-to-English cross-lingual links. The techniques described here can assist bi-lingual users where a particular topic is not covered in Chinese, is not equally covered in both languages, or is biased in one language; as well as for language learning.

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Nowadays people heavily rely on the Internet for information and knowledge. Wikipedia is an online multilingual encyclopaedia that contains a very large number of detailed articles covering most written languages. It is often considered to be a treasury of human knowledge. It includes extensive hypertext links between documents of the same language for easy navigation. However, the pages in different languages are rarely cross-linked except for direct equivalent pages on the same subject in different languages. This could pose serious difficulties to users seeking information or knowledge from different lingual sources, or where there is no equivalent page in one language or another. In this thesis, a new information retrieval task—cross-lingual link discovery (CLLD) is proposed to tackle the problem of the lack of cross-lingual anchored links in a knowledge base such as Wikipedia. In contrast to traditional information retrieval tasks, cross language link discovery algorithms actively recommend a set of meaningful anchors in a source document and establish links to documents in an alternative language. In other words, cross-lingual link discovery is a way of automatically finding hypertext links between documents in different languages, which is particularly helpful for knowledge discovery in different language domains. This study is specifically focused on Chinese / English link discovery (C/ELD). Chinese / English link discovery is a special case of cross-lingual link discovery task. It involves tasks including natural language processing (NLP), cross-lingual information retrieval (CLIR) and cross-lingual link discovery. To justify the effectiveness of CLLD, a standard evaluation framework is also proposed. The evaluation framework includes topics, document collections, a gold standard dataset, evaluation metrics, and toolkits for run pooling, link assessment and system evaluation. With the evaluation framework, performance of CLLD approaches and systems can be quantified. This thesis contributes to the research on natural language processing and cross-lingual information retrieval in CLLD: 1) a new simple, but effective Chinese segmentation method, n-gram mutual information, is presented for determining the boundaries of Chinese text; 2) a voting mechanism of name entity translation is demonstrated for achieving a high precision of English / Chinese machine translation; 3) a link mining approach that mines the existing link structure for anchor probabilities achieves encouraging results in suggesting cross-lingual Chinese / English links in Wikipedia. This approach was examined in the experiments for better, automatic generation of cross-lingual links that were carried out as part of the study. The overall major contribution of this thesis is the provision of a standard evaluation framework for cross-lingual link discovery research. It is important in CLLD evaluation to have this framework which helps in benchmarking the performance of various CLLD systems and in identifying good CLLD realisation approaches. The evaluation methods and the evaluation framework described in this thesis have been utilised to quantify the system performance in the NTCIR-9 Crosslink task which is the first information retrieval track of this kind.

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Graphene has promised many novel applications in nanoscale electronics and sustainable energy due to its novel electronic properties. Computational exploration of electronic functionality and how it varies with architecture and doping presently runs ahead of experimental synthesis yet provides insights into types of structures that may prove profitable for targeted experimental synthesis and characterization. We present here a summary of our understanding on the important aspects of dimension, band gap, defect, and interfacial engineering of graphene based on state-of-the-art ab initio approaches. Some most recent experimental achievements relevant for future theoretical exploration are also covered.

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Automated process discovery techniques aim at extracting models from information system logs in order to shed light into the business processes supported by these systems. Existing techniques in this space are effective when applied to relatively small or regular logs, but otherwise generate large and spaghetti-like models. In previous work, trace clustering has been applied in an attempt to reduce the size and complexity of automatically discovered process models. The idea is to split the log into clusters and to discover one model per cluster. The result is a collection of process models -- each one representing a variant of the business process -- as opposed to an all-encompassing model. Still, models produced in this way may exhibit unacceptably high complexity. In this setting, this paper presents a two-way divide-and-conquer process discovery technique, wherein the discovered process models are split on the one hand by variants and on the other hand hierarchically by means of subprocess extraction. The proposed technique allows users to set a desired bound for the complexity of the produced models. Experiments on real-life logs show that the technique produces collections of models that are up to 64% smaller than those extracted under the same complexity bounds by applying existing trace clustering techniques.