These are the logical costs of a signal detection task. It provided a way to generate never-before-seen data from cyclists at scale across a city in near real time-including road surface quality, cycle routes used, cycling blackspots and use of cycle paths. The user group was selected from more than 400 volunteers to provide a representative demographic sample. For each of these a detailed description of the approach is given together with an analysis of related and future work as appropriate. It is aimed primarily at researchers in the area of knowledge management and information retrieval and will also be a useful reference for students in computer science at the postgraduate level and for business managers who are aiming to increase the corporationsa information infrastructure. Within Computer Science and Artificial Intelligence, the term ontologies was coined in the Knowledge Sharing and Reuse Effort, for efficient engineering of distributed, cooperating knowledge-based systems.
An increasing amount of information is generated from the rapidly increasing number of sensor networks and smart devices. Software agents will be able to create automatically new services from already published services, with potentially huge implications for models of e-Business. The problem of making medical knowledge and medical data sharable over applications and reusable for several purposes is crucial. And semantic technology is used to enable service discovery. Other factors driving companies to try to manage and exploit their intellectual assets more effectively are increasing employee turnover rates and a more mobile workforce, which can lead to loss of knowledge, and globalization, often requiring people to collaborate and exchange knowledge across continents and time zones. Pérez Intelligent Software Components , V Ermolayev Cadence Design Systems GmbH , R Ghani Accenture Technology Labs , M Tilly European Microsoft Innovation Center , T Bösser kea pro , and A Imtiaz Forschungsinstitut für Rationalisierung Knowledge workers are central to an organisation's success, yet the tools they must use often stand in the way of maximising their productivity.
However, currently, Web Services are essentially described using semi-structured natural language mechanisms, which means that considerable human intervention is needed to find and combine Web Services into an end application. Although there are many algorithms for schema matching, little has been written about building a system that can be used in practice. Specifically, the paper discusses the use of knowledge discovery and human language technology to semi- automatically derive the required ontologies and meta-data, along with a methodology to support this process. Overall, this book mainly aims at researchers in academia and industry looking for a state-of-the-art overview of the use of semantic and Web 2. Users are organised into closed user groups or communities of interest with related or overlapping interests. The chapter shows how semantic technologies can make a contribution.
Early integration efforts focused on connectivity at the physical and syntactic layers. This paper describes the application of Internet-based three-dimensional 3-D user interfaces, comparing them with more traditional two-dimensional 2-D interfaces. Approach Emerging trends in knowledge access are considered followed by a description of how ontologies and semantics can contribute. Information Retrieval: Searching in the 21st Century focuses on core concepts, and current trends in the field. Semantic heterogeneity can arise at the schema level and at the data level. A main task of the prospective users, who interact directly with customers, is to understand customer requirements and translate those requirements into customer proposals.
The applications are designed to support professionals working in telecommunications to respond to customer requirements, for example to create customer proposals. Also required are basic functionalities such as the storage and management of semantic data and metadata. This method is different from other data matching or merging methods applied to database or data warehouse cleansing in that it employs more similarity measurements by exploring ontology features. We can measure this by expressing the market value of a company as a percentage of its book value. This implies that knowledge worker productivity is reduced and that organisations may be making decisions on the basis of incomplete knowledge. These enable sophisticated automatic support for acquiring, maintaining and accessing information. Four complementary technical advances are being integrated to create a coherent and domain-independent service delivery platform.
Most information retrieval technologies are designed to facilitate information discovery. Service-oriented architectures and service-orientation principles are being used to support the development of complex services based on distributed and reusable components. Web principles and technology are used to provide an underlying infrastructure that allows the integration of services at a world wide scale. This has to be done easily, without expecting people to spend time using an elaborate knowledge management system which requires information to be carefully categorized. An associated mobile app also lets cyclists customise their lights and send and receive low-battery, crash and theft alerts.
One domain where social media data can add value is transportation and traffic management. OntoShare: Evolving Ontologies in a Knowledge Sharing System J. The chapter also explains in some detail how user trials within the case study were used to validate our approach. We go onto describe proposed extensions to the Garden which would support and encourage the creation of communities of interest and the sharing of tacit knowledge. As well as sharing explicit codified knowledge, the sharing of tacit knowledge is encouraged via the automatic suggestion of, and support for, contact between people with mutual concerns or interests. We highlight one of several available transformational paths for traditional telecom operators to respond to challenges of declining revenues in their traditional business.
It looks at the key application areas: finding and organizing information; sharing knowledge; supporting processes, in particular informal processes; information integration; extracting knowledge from unstructured information; and finally sharing and reusing knowledge across organizations. While retaining the notions of directories and flles and providing all standard fllesystem operations, the semantics of these primitives are changed to modiflcations of the tag annotations. This article presents a novel definition of a declarative mapping language, which is able to map precisely and unambiguously the semantics of a domain conceptualization defined as an ontology into queries to a set of data sources, where the data is residing. A variety of research systems have been developed addressing some of the semantic issues. Ontology management is then the set of tools, techniques and technology for managing the resulting ontologies and associated metadata. So far, almost no one has addressed it.
Ontologies offer expressive power; they provide flexibility, with the ability to evolve dynamically unlike typical database schemata; and they make machine reasoning possible. We propose future directions for the Forum including cultural signposts that provide contextual cues in the intelligent community-based system to better support information sharing and real time communication between strangers. One of the key prerequisites for the Internet of Things IoT is interoperability. This allows more sophisticated analysis of documents: for example, named entity recognition is a language processing technique which can identify particular locations, organisations or people mentioned in textual documents with ontological descriptions of those entities. The impact of new internet trends Web 2.
Semantic heterogeneity is one of the key challenges in integrating and sharing data across disparate sources, data exchange and migration, data warehousing, model management, the Semantic Web and peer-to-peer databases. Model management is a generic approach to solving problems of data programmability where precisely engineered mappings are required. This paper describes a system which facilitates and encourages the sharing of knowledge between groups of users within or perhaps across organisations. Despite its explosive growth over the last decade, the Web remains essentially a tool to allow humans to access information. We outline the requirements and functionalities that were identified for a useful Semantic Desktop system and present an architecture that fulfills these requirements which was acquired by incremental refinement of the architecture of existing Semantic Desktop prototypes.