The Experts below are selected from a list of 3591 Experts worldwide ranked by ideXlab platform
Joseph G Davis - One of the best experts on this subject based on the ideXlab platform.
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computational and crowdsourcing methods for extracting Ontological Structure from folksonomy
International Semantic Web Conference, 2010Co-Authors: Joseph G DavisAbstract:This paper investigates the unification of folksonomies and ontologies in such a way that the resulting Structures can better support exploration and search on the World Wide Web. First, an integrated computational method is employed to extract the Ontological Structures from folksonomies. It exploits the power of low support association rule mining supplemented by an upper ontology such as WordNet. Promising results have been obtained from experiments using tag datasets from Flickr and Citeulike. Next, a crowdsourcing method is introduced to channel online users' search efforts to help evolve the extracted ontology.
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ESWC (2) - Computational and crowdsourcing methods for extracting Ontological Structure from folksonomy
Lecture Notes in Computer Science, 2010Co-Authors: Joseph G DavisAbstract:This paper investigates the unification of folksonomies and ontologies in such a way that the resulting Structures can better support exploration and search on the World Wide Web. First, an integrated computational method is employed to extract the Ontological Structures from folksonomies. It exploits the power of low support association rule mining supplemented by an upper ontology such as WordNet. Promising results have been obtained from experiments using tag datasets from Flickr and Citeulike. Next, a crowdsourcing method is introduced to channel online users' search efforts to help evolve the extracted ontology.
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ESWC - An Integrated Approach to Extracting Ontological Structures from Folksonomies
Lecture Notes in Computer Science, 2009Co-Authors: Joseph G Davis, Ying ZhouAbstract:Collaborative tagging systems have recently emerged as one of the rapidly growing web 2.0 applications. The informal social classification Structure in these systems, also known as folksonomy, provides a convenient way to annotate resources by allowing users to use any keyword or tag that they find relevant. In turn, the flat and non-hierarchical Structure with unsupervised vocabularies leads to low search precision and poor resource navigation and retrieval. This drawback has created the need for Ontological Structures which provide shared vocabularies and semantic relations for translating and integrating the different sources. In this paper, we propose an integrated approach for extracting Ontological Structure from folksonomies that exploits the power of low support association rule mining supplemented by an upper ontology such as WordNet.
Andreas Ekelhart - One of the best experts on this subject based on the ideXlab platform.
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Formalizing information security knowledge
Proceedings of the 4th International Symposium on Information Computer and Communications Security - ASIACCS '09, 2009Co-Authors: Stefan Fenz, Andreas EkelhartAbstract:Unified and formal knowledge models of the information security domain are fundamental requirements for supporting and enhancing existing risk management approaches. This paper describes a security ontology which provides an Ontological Structure for information security domain knowledge. Besides existing best-practice guidelines such as the German IT Grundschutz Manual also concrete knowledge of the considered organization is incorporated. An evaluation conducted by an information security expert team has shown that this knowledge model can be used to support a broad range of information security risk management approaches.
Karina Gibert - One of the best experts on this subject based on the ideXlab platform.
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Ontology-driven web-based semantic similarity
Journal of Intelligent Information Systems, 2010Co-Authors: David Sánchez, Montserrat Batet, Aida Valls, Karina GibertAbstract:Estimation of the degree of semantic similarity/distance between concepts is a very common problem in research areas such as natural language processing, knowledge acquisition, information retrieval or data mining. In the past, many similarity measures have been proposed, exploiting explicit knowledge—such as the Structure of a taxonomy—or implicit knowledge—such as information distribution. In the former case, taxonomies and/or ontologies are used to introduce additional semantics; in the latter case, frequencies of term appearances in a corpus are considered. Classical measures based on those premises suffer from some prob- lems: in the first case, their excessive dependency of the taxonomical/Ontological Structure; in the second case, the lack of semantics of a pure statistical analysis of occurrences and/or the ambiguity of estimating concept statistical distribution from term appearances. Measures based on Information Content (IC) of taxonomical concepts combine both approaches. However, they heavily depend on a properly pre-tagged and disambiguated corpus according to the Ontological entities in order to compute accurate concept appearance probabilities. This limits the applicability of those measures to other ontologies –like specific domain ontologies- and massive corpus –like the Web-. In this paper, several of the presented issues are analyzed. Modifications of classical similarity measures are also proposed. They are based on a contextualized and scalable version of IC computation in the Web by exploiting taxonomical knowledge. The goal is to avoid the measures’ dependency on the corpus pre-processing to achieve reliable results and minimize language ambiguity. Our proposals are able to outperform classical approaches when using the Web for estimating concept probabilities.
Patrick Lambrix - One of the best experts on this subject based on the ideXlab platform.
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repose an environment for repairing missing Ontological Structure
Asian Semantic Web Conference, 2009Co-Authors: Patrick LambrixAbstract:Developing ontologies is not an easy task and often the resulting ontologies are not consistent or complete. Such ontologies, although often useful, lead to problems when used in semantically-enabled applications.Wrong conclusions may be derived or valid conclusions may be missed. Defects in ontologies can take different forms. Syntactic defects are usually easy to find and to resolve. Defects regarding style include such things as unintended redundancy. More severe defects are the modeling defects which require domain knowledge to detect and resolve, and semantic defects such as unsatisfiable concepts and inconsistent ontologies.
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ASWC - RepOSE: An Environment for Repairing Missing Ontological Structure
The Semantic Web, 2009Co-Authors: Patrick LambrixAbstract:Developing ontologies is not an easy task and often the resulting ontologies are not consistent or complete. Such ontologies, although often useful, lead to problems when used in semantically-enabled applications.Wrong conclusions may be derived or valid conclusions may be missed. Defects in ontologies can take different forms. Syntactic defects are usually easy to find and to resolve. Defects regarding style include such things as unintended redundancy. More severe defects are the modeling defects which require domain knowledge to detect and resolve, and semantic defects such as unsatisfiable concepts and inconsistent ontologies.
Stefan Fenz - One of the best experts on this subject based on the ideXlab platform.
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mapping information security standard iso 27002 to an Ontological Structure
Information and Computer Security, 2016Co-Authors: Stefan Fenz, Stefanie Plieschnegger, Heidi HobelAbstract:Purpose The purpose of this paper is to increase the degree of automation within information security compliance projects by introducing a formal representation of the ISO 27002 standard. As information is becoming more valuable and the current businesses face frequent attacks on their infraStructure, enterprises need support at protecting their information-based assets. Design/methodology/approach Information security standards and guidelines provide baseline knowledge for protecting corporate assets. However, the efforts to check whether the implemented measures of an organization adhere to the proposed standards and guidelines are still significantly high. Findings This paper shows how the process of compliance checking can be supported by using machine-readable ISO 27002 control descriptions in combination with a formal representation of the organization’s assets. Originality/value The authors created a formal representation of the ISO 27002 standard and showed how a security ontology can be used to increase the efficiency of the compliance checking process.
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Formalizing information security knowledge
Proceedings of the 4th International Symposium on Information Computer and Communications Security - ASIACCS '09, 2009Co-Authors: Stefan Fenz, Andreas EkelhartAbstract:Unified and formal knowledge models of the information security domain are fundamental requirements for supporting and enhancing existing risk management approaches. This paper describes a security ontology which provides an Ontological Structure for information security domain knowledge. Besides existing best-practice guidelines such as the German IT Grundschutz Manual also concrete knowledge of the considered organization is incorporated. An evaluation conducted by an information security expert team has shown that this knowledge model can be used to support a broad range of information security risk management approaches.
