925 resultados para Semantic Web, Exploratory Search, Recommendation Systems
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Lecture 4: Ontological Hypertext and the Semantic Web Contains Powerpoint Lecture slides and Hypertext Research Papers: Conceptual linking: Ontology-based Open Hypermedia (Carr et al. 2001); CS AKTiveSpace: Building a Semantic Web Application (Glaser et al., 2004); The Semantic Web Revisited (Shadbolt, Hall and Berners-Lee, 2006); Mind the Semantic Gap (Millard et al., 2005).
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In this class, we will discuss metadata as well as current phenomena such as tagging and folksonomies. Readings: Ontologies Are Us: A Unified Model of Social Networks and Semantics, P. Mika, International Semantic Web Conference, 522-536, 2005. [Web link] Optional: Folksonomies: power to the people, E. Quintarelli, ISKO Italy-UniMIB Meeting, (2005)
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Slides and an essay on the Web Graph, search engines and how Google calculates Page Rank
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A resource for the teaching of concepts involved in 'web 3.0', including a powerpoint presentation with quiz, and accompanying tutorial
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Wednesday 2nd April 2014 Speaker(s): Stefan Decker Time: 02/04/2014 11:00-11:50 Location: B2/1083 File size: 897 Mb Abstract Ontologies have been promoted and used for knowledge sharing. Several models for representing ontologies have been developed in the Knowledge Representation field, in particular associated with the Semantic Web. In my talk I will summarise developments so far, and will argue that the currently advocated approaches miss certain basic properties of current distributed information sharing infrastructures (read: the Web and the Internet). I will sketch an alternative model aiming to support knowledge sharing and re-use on a global basis.
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The construction industry has incurred a considerable amount of waste as a result of poor logistics supply chain network management. Therefore, managing logistics in the construction industry is critical. An effective logistic system ensures delivery of the right products and services to the right players at the right time while minimising costs and rewarding all sectors based on value added to the supply chain. This paper reports on an on-going research study on the concept of context-aware services delivery in the construction project supply chain logistics. As part of the emerging wireless technologies, an Intelligent Wireless Web (IWW) using context-aware computing capability represents the next generation ICT application to construction-logistics management. This intelligent system has the potential of serving and improving the construction logistics through access to context-specific data, information and services. Existing mobile communication deployments in the construction industry rely on static modes of information delivery and do not take into account the worker’s changing context and dynamic project conditions. The major problems in these applications are lack of context-specificity in the distribution of information, services and other project resources, and lack of cohesion with the existing desktop based ICT infrastructure. The research works focus on identifying the context dimension such as user context, environmental context and project context, selection of technologies to capture context-parameters such wireless sensors and RFID, selection of supporting technologies such as wireless communication, Semantic Web, Web Services, agents, etc. The process of integration of Context-Aware Computing and Web-Services to facilitate the creation of intelligent collaboration environment for managing construction logistics will take into account all the necessary critical parameters such as storage, transportation, distribution, assembly, etc. within off and on-site project.
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Smart healthcare is a complex domain for systems integration due to human and technical factors and heterogeneous data sources involved. As a part of smart city, it is such a complex area where clinical functions require smartness of multi-systems collaborations for effective communications among departments, and radiology is one of the areas highly relies on intelligent information integration and communication. Therefore, it faces many challenges regarding integration and its interoperability such as information collision, heterogeneous data sources, policy obstacles, and procedure mismanagement. The purpose of this study is to conduct an analysis of data, semantic, and pragmatic interoperability of systems integration in radiology department, and to develop a pragmatic interoperability framework for guiding the integration. We select an on-going project at a local hospital for undertaking our case study. The project is to achieve data sharing and interoperability among Radiology Information Systems (RIS), Electronic Patient Record (EPR), and Picture Archiving and Communication Systems (PACS). Qualitative data collection and analysis methods are used. The data sources consisted of documentation including publications and internal working papers, one year of non-participant observations and 37 interviews with radiologists, clinicians, directors of IT services, referring clinicians, radiographers, receptionists and secretary. We identified four primary phases of data analysis process for the case study: requirements and barriers identification, integration approach, interoperability measurements, and knowledge foundations. Each phase is discussed and supported by qualitative data. Through the analysis we also develop a pragmatic interoperability framework that summaries the empirical findings and proposes recommendations for guiding the integration in the radiology context.
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This paper presents a hierarchical clustering method for semantic Web service discovery. This method aims to improve the accuracy and efficiency of the traditional service discovery using vector space model. The Web service is converted into a standard vector format through the Web service description document. With the help of WordNet, a semantic analysis is conducted to reduce the dimension of the term vector and to make semantic expansion to meet the user’s service request. The process and algorithm of hierarchical clustering based semantic Web service discovery is discussed. Validation is carried out on the dataset.
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One of the most pervasive classes of services needed to support e-Science applications are those responsible for the discovery of resources. We have developed a solution to the problem of service discovery in a Semantic Web/Grid setting. We do this in the context of bioinformatics, which is the use of computational and mathematical techniques to store, manage, and analyse the data from molecular biology in order to answer questions about biological phenomena. Our specific application is myGrid (www.mygrid.org.uk) that is developing open source, service-based middleware upon which bioinformatics applications can be built. myGrid is specifically targeted at developing open source high-level service Grid middleware for bioinformatics.
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One of the most pervasive classes of services needed to support e-Science applications are those responsible for the discovery of resources. We have developed a solution to the problem of service discovery in a Semantic Web/Grid setting. We do this in the context of bioinformatics, which is the use of computational and mathematical techniques to store, manage, and analyse the data from molecular biology in order to answer questions about biological phenomena. Our specific application is myGrid (http: //www.mygrid.org.uk) that is developing open source, service-based middleware upon which bioin- formatics applications can be built. myGrid is specif- ically targeted at developing open source high-level service Grid middleware for bioinformatics.
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Scientific workflows are becoming a valuable tool for scientists to capture and automate e-Science procedures. Their success brings the opportunity to publish, share, reuse and repurpose this explicitly captured knowledge. Within the myGrid project, we have identified key resources that can be shared including complete workflows, fragments of workflows and constituent services. We have examined the alternative ways these can be described by their authors (and subsequent users), and developed a unified descriptive model to support their later discovery. By basing this model on existing standards, we have been able to extend existing Web Service and Semantic Web Service infrastructure whilst still supporting the specific needs of the e-Scientist. myGrid components enable a workflow life-cycle that extends beyond execution, to include discovery of previous relevant designs, reuse of those designs, and subsequent publication. Experience with example groups of scientists indicates that this cycle is valuable. The growing number of workflows and services mean more work is needed to support the user in effective ranking of search results, and to support the repurposing process.
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Nowadays, the popularity of the Web encourages the development of Hypermedia Systems dedicated to e-learning. Nevertheless, most of the available Web teaching systems apply the traditional paper-based learning resources presented as HTML pages making no use of the new capabilities provided by the Web. There is a challenge to develop educative systems that adapt the educative content to the style of learning, context and background of each student. Another research issue is the capacity to interoperate on the Web reusing learning objects. This work presents an approach to address these two issues by using the technologies of the Semantic Web. The approach presented here models the knowledge of the educative content and the learner’s profile with ontologies whose vocabularies are a refinement of those defined on standards situated on the Web as reference points to provide semantics. Ontologies enable the representation of metadata concerning simple learning objects and the rules that define the way that they can feasibly be assembled to configure more complex ones. These complex learning objects could be created dynamically according to the learners’ profile by intelligent agents that use the ontologies as the source of their beliefs. Interoperability issues were addressed by using an application profile of the IEEE LOM- Learning Object Metadata standard.