Search (51 results, page 1 of 3)

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Abstract

The basic goal of education within a discipline is to transform a novice into an expert. This entails moving the novice toward the "semantic space" that the expert inhabits-the space of concepts, meanings, vocabularies, and other intellectual constructs that comprise the discipline. Metadata is significant to this goal in digitally mediated education environments. Encoding the experts' semantic space not only enables the sharing of semantics among discipline scientists, but also creates an environment that bridges the semantic gap between the common vocabulary of the novice and the granular descriptive language of the seasoned scientist (Greenberg, et al, 2005). Developments underlying the Semantic Web, where vocabularies are formalized in the Web Ontology Language (OWL), and Web 2.0 approaches of user-generated folksonomies provide an infrastructure for linking vocabulary systems and promoting group learning via metadata literacy. Group learning is a pedagogical approach to teaching that harnesses the phenomenon of "collective intelligence" to increase learning by means of collaboration. Learning a new semantic system can be daunting for a novice, and yet it is integral to advance one's knowledge in a discipline and retain interest. These ideas are key to the "BOT 2.0: Botany through Web 2.0, the Memex and Social Learning" project (Bot 2.0).72 Bot 2.0 is a collaboration involving the North Carolina Botanical Garden, the UNC SILS Metadata Research center, and the Renaissance Computing Institute (RENCI). Bot 2.0 presents a curriculum utilizing a memex as a way for students to link and share digital information, working asynchronously in an environment beyond the traditional classroom. Our conception of a memex is not a centralized black box but rather a flexible, distributed framework that uses the most salient and easiest-to-use collaborative platforms (e.g., Facebook, Flickr, wiki and blog technology) for personal information management. By meeting students "where they live" digitally, we hope to attract students to the study of botanical science. A key aspect is to teach students scientific terminology and about the value of metadata, an inherent function in several of the technologies and in the instructional approach we are utilizing. This poster will report on a study examining the value of both folksonomies and taxonomies for post-secondary college students learning plant identification. Our data is drawn from a curriculum involving a virtual independent learning portion and a "BotCamp" weekend at UNC, where students work with digital plan specimens that they have captured. Results provide some insight into the importance of collaboration and shared vocabulary for gaining confidence and for student progression from novice to expert in botany.

Source

Metadata for semantic and social applications : proceedings of the International Conference on Dublin Core and Metadata Applications, Berlin, 22 - 26 September 2008, DC 2008: Berlin, Germany / ed. by Jane Greenberg and Wolfgang Klas

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LCSH

Artificial intelligence
Artificial Intelligence (incl. Robotics)

Subject

Artificial intelligence
Artificial Intelligence (incl. Robotics)

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Abstract

Die historischen Wurzeln des Semantic Web reichen zurück in die Artificial Intelligence Forschung der 1960er und -70er Jahre. Konzepte aus der Light Weight Artificial Intelligence wie Frames, Microworlds und Heuristic Programming stellten erste Versuche der maschinenverarbeitbaren Wissensrepräsentation dar. Hier ging es nicht darum, intelligentes Verhalten zu simulieren, sondern Methoden zu entwickeln, die den Menschen in seiner Entscheidungsfindung unterstützen. Durch die inhaltliche Beschreibung (semantische Anreicherung) von Datenbeständen mit maschinenlesbaren Metadaten und Scripts wurden Maschinen in die Lage versetzt autonom Daten zu verarbeiten. Der Computer sollte in der Lage sein, den Kontext, in dem Daten erzeugt und abgelegt werden, zu "verstehen" und darauf basierend für den Nutzer relevante Daten zu selektieren, zu verarbeiten und auszugeben.

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LCSH

Artificial intelligence

Subject

Artificial intelligence

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LCSH

Artificial intelligence

Subject

Artificial intelligence

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Artificial intelligence

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Artificial intelligence

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LCSH

Artificial intelligence
Artificial Intelligence (incl. Robotics)

Subject

Artificial intelligence
Artificial Intelligence (incl. Robotics)

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Abstract

Primitive thinking forms affected the organization of knowledge, and at a later date writing also affected organization. Currently, the web requires new forms of learning and knowledge; with the globalization of information, connectivity and virtuality have a bearing on human thought. Digital thinking is shaping our reality and its organizational form. Natural memory, considered to be a process that requires the structure of natural language and human capabilities, is interwoven with a subject and a conscience; memory preserved through writing required other tools to assist it, and classifications, cataloguing, organization or other KOS were created. The new tool for recovering digital memory is the semantic web. This points to information's future on the Internet and seems to approach the utopia of global, organized information and attempts to give the website greater significance. The Web 3.0 incorporates a proliferation of languages, concepts and tools that are difficult to govern and are created by users. The semantic web seems to be a natural evolution of the participative web in which we find ourselves, and if an effective combination is achieved between the inclusion of semantic content in web pages and the use of artificial intelligence it will be a revolution; semantic codification will be a fact when it is totally automated. Based on this, a collective digital intelligence is being constituted. We find ourselves before intelligent multitudes with broad access to enormous amounts of information. The intelligent multitude emerges when technologies interconnect. In this global interconnection of semantic information an exponential pattern of technological growth can take place.

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Artificial intelligence

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Artificial intelligence

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Artificial intelligence

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Artificial intelligence

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Content

Vgl.: http%3A%2F%2Fdigbib.ubka.uni-karlsruhe.de%2Fvolltexte%2Fdocuments%2F1627&ei=tAtYUYrBNoHKtQb3l4GYBw&usg=AFQjCNHeaxKkKU3-u54LWxMNYGXaaDLCGw&sig2=8WykXWQoDKjDSdGtAakH2Q&bvm=bv.44442042,d.Yms.

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Date

22. 9.2007 15:41:14

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Artificial intelligence

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Artificial intelligence

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Artificial intelligence

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Artificial intelligence

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22. 9.2007 15:41:14

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Date

22. 9.2007 15:41:14

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Abstract

The two-volume set LNCS 6496 and 6497 constitutes the refereed proceedings of the 9th International Semantic Web Conference, ISWC 2010, held in Shanghai, China, during November 7-11, 2010. Part I contains 51 papers out of 578 submissions to the research track. Part II contains 18 papers out of 66 submissions to the semantic Web in-use track, 6 papers out of 26 submissions to the doctoral consortium track, and also 4 invited talks. Each submitted paper were carefully reviewed. The International Semantic Web Conferences (ISWC) constitute the major international venue where the latest research results and technical innovations on all aspects of the Semantic Web are presented. ISWC brings together researchers, practitioners, and users from the areas of artificial intelligence, databases, social networks, distributed computing, Web engineering, information systems, natural language processing, soft computing, and human computer interaction to discuss the major challenges and proposed solutions, the success stories and failures, as well the visions that can advance research and drive innovation in the Semantic Web.

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Abstract

The Semantic Web has been criticized for not being semantic. This article examines the questions of why and how the Web of Data, expressed in the Resource Description Framework (RDF), has come to be known as the Semantic Web. Contrary to previous papers, we deliberately take a descriptive stance and do not start from preconceived ideas about the nature of semantics. Instead, we mainly base our analysis on early design documents of the (Semantic) Web. The main determining factor is shown to be link typing, coupled with the influence of online metadata. Both factors already were present in early web standards and drafts. Our findings indicate that the Semantic Web is directly linked to older artificial intelligence work, despite occasional claims to the contrary. Because of link typing, the Semantic Web can be considered an example of a semantic network. Originally network representations of the meaning of natural language utterances, semantic networks have eventually come to refer to any networks with typed (usually directed) links. We discuss possible causes for this shift and suggest that it may be due to confounding paradigmatic and syntagmatic semantic relations.

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Abstract

The increasingly pervasive nature of the Web, expanding to devices and things in everydaylife, along with new trends in Artificial Intelligence call for new paradigms and a new look onKnowledge Representation and Processing at scale for the Semantic Web. The emerging, but stillto be concretely shaped concept of "Knowledge Graphs" provides an excellent unifying metaphorfor this current status of Semantic Web research. More than two decades of Semantic Webresearch provides a solid basis and a promising technology and standards stack to interlink data,ontologies and knowledge on the Web. However, neither are applications for Knowledge Graphsas such limited to Linked Open Data, nor are instantiations of Knowledge Graphs in enterprises- while often inspired by - limited to the core Semantic Web stack. This report documents theprogram and the outcomes of Dagstuhl Seminar 18371 "Knowledge Graphs: New Directions forKnowledge Representation on the Semantic Web", where a group of experts from academia andindustry discussed fundamental questions around these topics for a week in early September 2018,including the following: what are knowledge graphs? Which applications do we see to emerge?Which open research questions still need be addressed and which technology gaps still need tobe closed?

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Source

Metadata and semantics research: 10th International Conference, MTSR 2016, Göttingen, Germany, November 22-25, 2016, Proceedings. Eds.: E. Garoufallou