Search (130 results, page 1 of 7)

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Abstract

This article shows how a fuzzy ontology-based approach can improve semantic documents retrieval. After formally defining a fuzzy ontology and a fuzzy knowledge base, a special type of new fuzzy relationship called (semantic) correlation, which links the concepts or entities in a fuzzy ontology, is discussed. These correlations, first assigned by experts, are updated after querying or when a document has been inserted into a database. Moreover, in order to define a dynamic knowledge of a domain adapting itself to the context, it is shown how to handle a tradeoff between the correct definition of an object, taken in the ontology structure, and the actual meaning assigned by individuals. The notion of a fuzzy concept network is extended, incorporating database objects so that entities and documents can similarly be represented in the network. Information retrieval (IR) algorithm, using an object-fuzzy concept network (O-FCN), is introduced and described. This algorithm allows us to derive a unique path among the entities involved in the query to obtain maxima semantic associations in the knowledge domain. Finally, the study has been validated by querying a database using fuzzy recall, fuzzy precision, and coefficient variant measures in the crisp and fuzzy cases.

Date

9.11.2008 13:07:29

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Content

One of a series of three publications influenced by the travelling exhibit Places & Spaces: Mapping Science, curated by the Cyberinfrastructure for Network Science Center at Indiana University. - Additional materials can be found at http://http://scimaps.org/atlas2. Erweitert durch: Börner, Katy. Atlas of Science: Visualizing What We Know.

Date

22. 1.2017 16:54:03
22. 1.2017 17:10:56

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Content

Vgl.: https%3A%2F%2Faclanthology.org%2FD19-5317.pdf&usg=AOvVaw0ZZFyq5wWTtNTvNkrvjlGA.

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Date

2. 3.2013 12:29:05

Source

Wissensspeicher in digitalen Räumen: Nachhaltigkeit - Verfügbarkeit - semantische Interoperabilität. Proceedings der 11. Tagung der Deutschen Sektion der Internationalen Gesellschaft für Wissensorganisation, Konstanz, 20. bis 22. Februar 2008. Hrsg.: J. Sieglerschmidt u. H.P.Ohly

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Date

29. 7.2011 14:44:56
26.12.2011 13:40:22

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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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Content

Submitted in partial fulfillment of the requirements for the degree of Doctor of Philosophy in Language and Information Technologies. Vgl.: https%3A%2F%2Fwww.cs.cmu.edu%2F~cx%2Fpapers%2Fknowledge_based_text_representation.pdf&usg=AOvVaw0SaTSvhWLTh__Uz_HtOtl3.

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Abstract

Internet of Things (IoT) brings the third development wave of the global information industry which makes users, network and perception devices cooperate more closely. However, if IoT has security problems, it may cause a variety of damage and even threaten human lives and properties. To improve the abilities of monitoring, providing emergency response and predicting the development trend of IoT security, a new paradigm called network security situation awareness (NSSA) is proposed. However, it is limited by its ability to mine and evaluate security situation elements from multi-source heterogeneous network security information. To solve this problem, this paper proposes an IoT network security situation awareness model using situation reasoning method based on semantic ontology and user-defined rules. Ontology technology can provide a unified and formalized description to solve the problem of semantic heterogeneity in the IoT security domain. In this paper, four key sub-domains are proposed to reflect an IoT security situation: context, attack, vulnerability and network flow. Further, user-defined rules can compensate for the limited description ability of ontology, and hence can enhance the reasoning ability of our proposed ontology model. The examples in real IoT scenarios show that the ability of the network security situation awareness that adopts our situation reasoning method is more comprehensive and more powerful reasoning abilities than the traditional NSSA methods. [http://ieeexplore.ieee.org/abstract/document/7999187/]

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Abstract

Knowledge network construction (KNC) is the essence of dynamic knowledge architecture, and is helpful to illustrate ubiquitous knowledge service in digital libraries (DLs). The authors explore its theoretical foundations and basic rules to elucidate the basic principles of KNC in DLs. The results indicate that world general connection, small-world phenomenon, relevance theory, unity and continuity of science development have been the production tool, architecture aim and scientific foundation of KNC in DLs. By analyzing both the characteristics of KNC based on different types of knowledge linking and the relationships between different forms of knowledge and the appropriate ways of knowledge linking, the basic principle of KNC is summarized as follows: let each kind of knowledge linking form each shows its ability, each kind of knowledge manifestation each answer the purpose intended in practice, and then subjective knowledge network and objective knowledge network are organically combined. This will lay a solid theoretical foundation and provide an action guide for DLs to construct knowledge networks.

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Abstract

The term "social network" was first mentioned in 1954 by J.A. Barnes. The social network is a structure that consists of nodes; the nodes represent individual people or organizations. Such a structure depicts the ways in which people are connected through diverse social familiarities like acquaintance, friendship or close familiar bonds.

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Date

4. 9.2011 12:29:09

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Abstract

Detecting science-technology hierarchical linkages is beneficial for understanding deep interactions between science and technology (S&T). Previous studies have mainly focused on linear linkages between S&T but ignored their structural linkages. In this paper, we propose a network coupling approach to inspect hierarchical interactions of S&T by integrating their knowledge linkages and structural linkages. S&T knowledge networks are first enhanced with bidirectional encoder representation from transformers (BERT) knowledge alignment, and then their hierarchical structures are identified based on K-core decomposition. Hierarchical coupling preferences and strengths of the S&T networks over time are further calculated based on similarities of coupling nodes' degree distribution and similarities of coupling edges' weight distribution. Extensive experimental results indicate that our approach is feasible and robust in identifying the coupling hierarchy with superior performance compared to other isomorphism and dissimilarity algorithms. Our research extends the mindset of S&T linkage measurement by identifying patterns and paths of the interaction of S&T hierarchical knowledge.

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Abstract

Discovering relationships among concepts and categories is crucial in various information systems. The authors' objective was to discover such relationships among document categories. Traditionally, such relationships are represented in the form of a concept hierarchy, grouping some categories under the same parent category. Although the nature of hierarchy supports the identification of categories that may share the same parent, not all of these categories have a relationship with each other - other than sharing the same parent. However, some non-sibling relationships exist that although are related to each other are not identified as such. The authors identify and build a relationship network (relationship-net) with categories as the vertices and relationships as the edges of this network. They demonstrate that using a relationship-net, some nonobvious category relationships are detected. Their approach capitalizes on the misclassification information generated during the process of text classification to identify potential relationships among categories and automatically generate relationship-nets. Their results demonstrate a statistically significant improvement over the current approach by up to 73% on 20 News groups 20NG, up to 68% on 17 categories in the Open Directories Project (ODP17), and more than twice on ODP46 and Special Interest Group on Information Retrieval (SIGIR) data sets. Their results also indicate that using misclassification information stemming from passage classification as opposed to document classification statistically significantly improves the results on 20NG (8%), ODP17 (5%), ODP46 (73%), and SIGIR (117%) with respect to F1 measure. By assigning weights to relationships and by performing feature selection, results are further optimized.

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LCSH

Computer network architectures

Subject

Computer network architectures

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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 Future of Information Architecture examines issues surrounding why information is processed, stored and applied in the way that it has, since time immemorial. Contrary to the conventional wisdom held by many scholars in human history, the recurrent debate on the explanation of the most basic categories of information (eg space, time causation, quality, quantity) has been misconstrued, to the effect that there exists some deeper categories and principles behind these categories of information - with enormous implications for our understanding of reality in general. To understand this, the book is organised in to four main parts: Part I begins with the vital question concerning the role of information within the context of the larger theoretical debate in the literature. Part II provides a critical examination of the nature of data taxonomy from the main perspectives of culture, society, nature and the mind. Part III constructively invesitgates the world of information network from the main perspectives of culture, society, nature and the mind. Part IV proposes six main theses in the authors synthetic theory of information architecture, namely, (a) the first thesis on the simpleness-complicatedness principle, (b) the second thesis on the exactness-vagueness principle (c) the third thesis on the slowness-quickness principle (d) the fourth thesis on the order-chaos principle, (e) the fifth thesis on the symmetry-asymmetry principle, and (f) the sixth thesis on the post-human stage.

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Abstract

The quantitative evaluation of thesauri has been carried out much further since 1976. This type of evaluation is based on counting of special factors in thesaurus structure, some of which are counting preferred terms, non preferred terms, cross reference terms and so on. Therefore, various statistical tests have been proposed and applied for evaluation of thesauri. In this article, we try to explain some ratios in the field of unity quantitative evaluation in a thesaurus term network. Theoretical base of the ratios' indicators and indices construction, and epistemological thought in this type of quantitative evaluation, are discussed in this article. The theoretical base of quantitative evaluation is the epistemological thought of Immanuel Kant's Critique of pure reason. The cognition states of transcendental understanding are divided into three steps, the first is perception, the second combination and the third, relation making. Terms relation domains and conceptual relation domains can be analyzed with ratios. The use of quantitative evaluations in current research in the field of thesaurus construction prepares a basis for a restoration period. In modern thesaurus construction, traditional term relations are analyzed in detail in the form of new conceptual relations. Hence, the new domains of hierarchical and associative relations are constructed in the form of relations between concepts. The newly formed conceptual domains can be a suitable basis for quantitative evaluation analysis in conceptual relations.

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Date

29. 6.2015 14:55:01
29. 6.2015 16:09:05

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Abstract

The presentation will briefly introduce a series of major principles for bringing subject terminology to the network level. A closer look at one KOS in particular, the Dewey Decimal Classification, should help to gain more insight into the perceived difficulties and potential benefits of building taxonomy services out and on top of classic large-scale vocabularies or taxonomies.

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Date

20.12.2018 12:39:29