939 resultados para Open Information Extraction
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Thesis (Master's)--University of Washington, 2016-06
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The potential of online learning has long afforded the hope of providing quality education to anyone, anywhere in the world. The recent development of Massive Open Online Courses (MOOCs) heralded an exciting new breakthrough by providing free academic instruction and professional skills development from the world’s leading universities to anyone with the sufficient resources to access the internet. The research in Advancing MOOCs for Development Initiative study was designed to analyze the MOOC landscape in developing countries and to better understand the motivations of MOOC users and afford insights on the advantages and limitations of MOOCs for workforce development outcomes. The key findings of this study challenge commonly held beliefs about MOOC usage in developing countries, defying typical characterizations of how people in resource constrained settings use technology for learning and employment. In fact, some of the findings are so contrary to what has been reported in the U.S. and other developed environments that they raise new questions for further investigation.
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Integrating information in the molecular biosciences involves more than the cross-referencing of sequences or structures. Experimental protocols, results of computational analyses, annotations and links to relevant literature form integral parts of this information, and impart meaning to sequence or structure. In this review, we examine some existing approaches to integrating information in the molecular biosciences. We consider not only technical issues concerning the integration of heterogeneous data sources and the corresponding semantic implications, but also the integration of analytical results. Within the broad range of strategies for integration of data and information, we distinguish between platforms and developments. We discuss two current platforms and six current developments, and identify what we believe to be their strengths and limitations. We identify key unsolved problems in integrating information in the molecular biosciences, and discuss possible strategies for addressing them including semantic integration using ontologies, XML as a data model, and graphical user interfaces as integrative environments.
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As with all new ideas, the concept of Open Innovation requires extensive empirical investigation, testing and development. This paper analyzes Procter and Gamble's 'Connect and Develop' strategy as a case study of the major organizational and technological changes associated with open innovation. It argues that although some of the organizational changes accompanying open innovation are beginning to be described in the literature, more analysis is warranted into the ways technological changes have facilitated open innovation strategies, particularly related to new product development. Information and communications technologies enable the exchange of distributed sources of information in the open innovation process. The case study shows that furthermore a suite of new technologies for data mining, simulation, prototyping and visual representation, what we call 'innovation technology', help to support open innovation in Procter and Gamble. The paper concludes with a suggested research agenda for furthering understanding of the role played by and consequences of this technology.
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The road to electric rope shovel automation is marked with technological innovations that include an increase in operational information available to mining operations. The CRCMining Shovel Operator Information System not only collects machine operational data but also provides the operator with knowledge-of-performance and influences his/her performance to achieve higher productivity with reduced machine duty. The operator’s behaviour is one of the most important aspects of the man-machine interaction to be considered before semi- or fully-automated shovel systems can be realised. This paper presents the results of the rope shovel studies conducted by CRCMining between 2002 and 2004, provides information on current research to improve shovel performance and briefly discusses the implications of human-system interactions on future designs of autonomous machines.
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Lots of work has been done in texture feature extraction for rectangular images, but not as much attention has been paid to the arbitrary-shaped regions available in region-based image retrieval (RBIR) systems. In This work, we present a texture feature extraction algorithm, based on projection onto convex sets (POCS) theory. POCS iteratively concentrates more and more energy into the selected coefficients from which texture features of an arbitrary-shaped region can be extracted. Experimental results demonstrate the effectiveness of the proposed algorithm for image retrieval purposes.
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This paper presents the creation of 3D statistical shape models of the knee bones and their use to embed information into a segmentation system for MRIs of the knee. We propose utilising the strong spatial relationship between the cartilages and the bones in the knee by embedding this information into the created models. This information can then be used to automate the initialisation of segmentation algorithms for the cartilages. The approach used to automatically generate the 3D statistical shape models of the bones is based on the point distribution model optimisation framework of Davies. Our implementation of this scheme uses a parameterized surface extraction algorithm, which is used as the basis for the optimisation scheme that automatically creates the 3D statistical shape models. The current approach is illustrated by generating 3D statistical shape models of the patella, tibia and femoral bones from a segmented database of the knee. The use of these models to embed spatial relationship information to aid in the automation of segmentation algorithms for the cartilages is then illustrated.
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Information and content integration are believed to be a possible solution to the problem of information overload in the Internet. The article is an overview of a simple solution for integration of information and content on the Web. Previous approaches to content extraction and integration are discussed, followed by introduction of a novel technology to deal with the problems, based on XML processing. The article includes lessons learned from solving issues of changing webpage layout, incompatibility with HTML standards and multiplicity of the results returned. The method adopting relative XPath queries over DOM tree proves to be more robust than previous approaches to Web information integration. Furthermore, the prototype implementation demonstrates the simplicity that enables non-professional users to easily adopt this approach in their day-to-day information management routines.
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Machine learning techniques for prediction and rule extraction from artificial neural network methods are used. The hypothesis that market sentiment and IPO specific attributes are equally responsible for first-day IPO returns in the US stock market is tested. Machine learning methods used are Bayesian classifications, support vector machines, decision tree techniques, rule learners and artificial neural networks. The outcomes of the research are predictions and rules associated With first-day returns of technology IPOs. The hypothesis that first-day returns of technology IPOs are equally determined by IPO specific and market sentiment is rejected. Instead lower yielding IPOs are determined by IPO specific and market sentiment attributes, while higher yielding IPOs are largely dependent on IPO specific attributes.