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Symposium on Learning, knowledge, and Adaptivity 2011, LWA 2011

作者： Benz, Dominik Körner, Christian Hotho, Andreas Stumme, Gerd Strohmaier, Markus Knowledge and Data Engineering Group University of Kassel Germany Knowledge Management Institute Graz University of Technology Austria Data Mining and Information Retrieval Group University of Wurzburg Germany

Recent research has demonstrated how the widespread adoption of collaborative tagging systems yields emergent semantics. In recent years, much has been learned about how to harvest the data produced by taggers for engineering light-weight ontologies. For example, existing measures of tag similarity and tag relatedness have proven crucial step stones for making latent semantic relations in tagging systems explicit. However, little progress has been made on other issues, such as understanding the different levels of tag generality (or tagabstrcatsness), which is essential for, among others, identifying hierarchical relationships between concepts. In this paper we aim to address this gap. Starting from a review of linguistic definitions of wordabstrcatness, we first use several large-scale ontologies and taxonomies as grounded measures of word generality, including Yago, Wordnet, DMOZ and Wikitaxonomy. Then, we introduce and apply several folksonomy-based methods to measure the level of generality of given tags. We evaluate these methods by comparing them with the grounded measures. Our results suggest that the generality of tags in social tagging systems can be approximated with simple measures. Our work has implications for a number of problems related to social tagging systems, including search, tag recommendation, and the acquisition of light-weight ontologies from tagging data.

关键词： Ontology

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Stop thinking, start tagging: Tag semantics emerge from collaborative verbosity 10

Stop thinking, start tagging: Tag semantics emerge from coll...

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19th International World Wide Web Conference, WWW2010

作者： Körner, Christian Benz, Dominik Hotho, Andreas Strohmaier, Markus Stumme, Gerd Knowledge Management Institute Graz University of Technology Graz Austria Knowledge and Data Engineering Group University of Kassel Kassel Germany Data Mining and Information Retrieval Group University of Würzburg Würzburg Germany Knowledge Management Institute Know-Center Graz University of Technology Graz Austria

ISBN: (纸本)9781605587998

Recent research provides evidence for the presence of emergent semantics in collaborative tagging systems. While several methods have been proposed, little is known about the factors that influence the evolution of semantic structures in these systems. A natural hypothesis is that the quality of the emergent semantics depends on the pragmatics of tagging: Users with certain usage patterns might contribute more to the resulting semantics than others. In this work, we propose several measures which enable a pragmatic differentiation of taggers by their degree of contribution to emerging semantic structures. We distinguish between categorizers, who typically use a small set of tags as a replacement for hierarchical classification schemes, and describers, who are annotating resources with a wealth of freely associated, descriptive keywords. To study our hypothesis, we apply semantic similarity measures to 64 different partitions of a real-world and large-scale folksonomy containing different ratios of categorizers and describers. Our results not only show that "verbose" taggers are most useful for the emergence of tag semantics, but also that a subset containing only 40% of the most 'verbose' taggers can produce results that match and even outperform the semantic precision obtained from the whole dataset. Moreover, the results suggest that there exists a causal link between the pragmatics of tagging and resulting emergent semantics. This work is relevant for designers and analysts of tagging systems interested (i) in fostering the semantic development of their platforms, (ii) in identifying users introducing "semantic noise", and (iii) in learning ontologies. © 2010 International World Wide Web Conference Committee (IW3C2).

关键词： Semantics

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How tagging pragmatics influence tag sense discovery in social annotation systems

How tagging pragmatics influence tag sense discovery in soci...

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35th European Conference on Information Retrieval, ECIR 2013

作者： Niebler, Thomas Singer, Philipp Benz, Dominik Körner, Christian Strohmaier, Markus Hotho, Andreas Data Mining and Information Retrieval Group University of Würzburg 97074 Würzburg Germany Knowledge Management Institute Graz University of Technology 8010 Graz Austria Knowledge and Data Engineering Group University of Kassel 34121 Kassel Germany

ISBN: (纸本)9783642369728

The presence of emergent semantics in social annotation systems has been reported in numerous studies. Two important problems in this context are the induction of semantic relations among tags and the discovery of different senses of a given tag. While a number of approaches for discovering tag senses exist, little is known about which factors influence the discovery process. In this paper, we analyze the influence of user pragmatic factors. We divide taggers into different pragmatic distinctions. Based on these distinctions, we identify subsets of users whose annotations allow for a more precise and complete discovery of tag senses. Our results provide evidence for a link between tagging pragmatics and semantics and provide another argument for including pragmatic factors in semantic extraction methods. Our work is relevant for improving search, retrieval and browsing in social annotation systems, as well as for optimizing ontology learning algorithms based on tagging data. © 2013 Springer-Verlag.

关键词： Semantics

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GTMalpha - Towards a graphical notation for topic maps

GTMalpha - Towards a graphical notation for topic maps

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4th International Conference on Topic Maps Research and Applications, TMRA 2008

作者： Thomas, Hendrik Redmann, Tobias Pressler, Maik Markscheffel, Bernd Knowledge and Data Engineering Group School of Computer Science and Statistics Trinity College Dublin Ireland Department of Information and Knowledge Management Faculty of Economic Sciences Ilmenau University of Technology Germany

ISBN: (纸本)9783941152052

In the last years several drafts, recommendations and concepts for a graphical notation for Topic Maps have been published, but till today no graphical notation is generally approved and used in the Topic Maps community. In this paper we present GTMalpha as a conceptual new notation for a graphical representation of Topic Maps. Our objective is, to provide a practical usable notation, which allows a complete, consistent as well as easy to use graphical representation of any given topic map draft. GTMalpha provides a domain as well as a subject centric view and most important it considers the unique characteristics of the Topic Maps paradigm. This paper serves as a user oriented GTMalpha manual for ontology designers, domain experts as well as users.

关键词： Ontology

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Modeling of discrete event systems: A holistic and incremental approach using Petri nets

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ACM Transactions on Modeling and Computer Simulation 2004年第4期14卷 389-423页

作者： Bobeanu, Carmen-Veronica Kerckhoffs, Eugene J. H. Van Landeghem, Hendrik Ghent University Delft University of Technology Ghent University Department Industrial Management Technologiepark 903 B-9052 Ghent Belgium Delft University of Technology Mediamatica Department Data and Knowledge Engineering Group Mekelweg 4 2628 CD Delft Netherlands

In this article, the authors provide an alternative view on Petri nets modeling of discrete event systems. The proposed modeling procedure follows the Systems Specification guidelines underlying the well-known DEVS modeling formalism. The authors' endeavour is towards perfecting the design of reusable Petri nets-based models by searching for a good primitive for a modular model construction and the introduction of coupling templates as standardised means to couple building block components. Assuming that the real-world system to be modeled has been analyzed in depth beforehand through a suitable system analysis method (which itself is beyond the scope of the article), we present a systematic step-by-step approach to construct a model in the Petri nets domain together with its experimental frame. The construction adheres to well-defined rules, which enable computer-based model construction. The input for this systematic bottom-up construction of Petri nets-models is information (about, e.g., primitive system components, entity flows, routing constructs) gathered from the top-down system analysis. In the article, attention is also paid to the algebraic backgrounds underlying the proposed model construction. These provide the basis for formal correctness proofs, mapping Petri nets onto DEVS-models, and complexity reduction of the found Petri nets-models. By offering to the model builder the possibility to handle multiple abstraction levels and by addressing important issues related to the interfacing question of coupled models and model components described in Petri nets and DEVS formalism, the authors' work addresses two of the main research directions of Computer Automated Multi-Paradigm Modeling ([Mosterman and Vangheluwe 2002]): model abstraction and multiformalism modeling. The article concludes with an illustrative application example.

关键词： Petri nets

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From subjects to concept clouds-Why semantic mapping is necessary

From subjects to concept clouds-Why semantic mapping is nece...

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1st International Workshop on knowledge Federation 2008

作者： Thomas, Hendrik Markscheffel, Bernd Redmann, Tobias Department of Information-and Knowledge Management TechnischeUniversität Ilmenau P.O. Box 100565 98693 Ilmenau Germany Knowledge / Data Engineering Group School of Computer Science and Statistics Trinity College Dublin Ireland

To realize the vision of the semantic web it is essential to be able to exchange formal modeled knowledge between applications and humans without loss of meaning. In this paper, we focus on questions relating to meaning, interpretation and subject identity in modern semantic web languages. Based on the semiotic triangle we show that topics as well as RDF resources are symbols, representing concepts and not referents as the common term "subject" would indicate. A subject can not be represented as a single entity, but rather as a complex and evolving system of different concepts. Based on this insight we explain how the resulting plurality and uncertainness of the interpretation of symbols can be handled using semantic mappings. By defining transformation rules, the exchange and integration of knowledge from different semantic models becomes possible. Concluding we define recommendations and design guidelines for a semantic mapping management system, which is needed to support users and applications in creating, reusing, managing and applying such semantic mappings.

关键词： Mapping

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Ubiquitous Social Media Analysis 1

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丛书名： Lecture Notes in Computer Science

1000年

作者： Martin Atzmueller Alvin Chin Denis Helic Andreas Hotho

ISBN: (数字)9783642453922

ISBN: (纸本)9783642453915

This book constitutes the thoroughly refereed joint post-proceedings of the Third International Workshop on Mining Ubiquitous and Social Environments, MUSE 2012, held in Bristol, UK, in September 2012, and the Third International Workshop on Modeling Social Media, MSM 2012, held in Milwaukee, WI, USA, in June 2012. The 8 full papers included in the book are revised and significantly extended versions of papers submitted to the workshops. They cover a wide range of topics organized in three main themes: communities and group structure in ubiquitous social media; ubiquitous modeling and aspects of social interactions and influence.

关键词： Information Storage and Retrieval data Mining and knowledge Discovery Discrete Mathematics in Computer Science Artificial Intelligence

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User needs for enhanced engagement with cultural heritage collections

User needs for enhanced engagement with cultural heritage co...

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2nd International Conference on Theory and Practice of Digital Libraries, TPDL 2012

作者： Sweetnam, Mark S. Agosti, Maristella Orio, Nicola Ponchia, Chiara Steiner, Christina M. Hillemann, Eva-Catherine Ó Siochrú, Micheál Lawless, Séamus Department of History Trinity College Dublin Ireland Department of Information Engineering University of Padua Italy Department of Cultural Heritage University of Padua Italy Knowledge Management Institute Graz University of Technology Austria Knowledge and Data Engineering Group Trinity College Dublin Ireland

ISBN: (纸本)9783642332890

This paper presents research carried out in order to elicit user needs for the design and development of a digital library and research platform intended to enhance user engagement with cultural heritage collections. It outlines a range of user constituencies for this digital library. The paper outlines a taxonomy of intended users for this system and describes in detail the characteristics and requirements of these users for the facilitation and enhancement of their engagement with and use of textual and visual cultural artefacts. © 2012 Springer-Verlag.

关键词： Digital libraries

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Text Classification by Boosting Weak Learners Based on Terms and Concepts

Text Classification by Boosting Weak Learners Based on Terms...

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Fourth IEEE International Conference on data Mining

作者： Stephan Bloehdorn Andreas Hotho Institute AIFB Knowledge Management Group University of Karlsruhe Karlsruhe Germany Knowledge and Data Engineering Group University of Kassel Kassel Germany

Document representations for text classification are typically based on the classical Bag-Of-Words paradigm. This approach comes with deficiencies that motivate the integration of features on a higher semantic level than single words. In this paper we propose an enhancement of the classical document representation through concepts extracted from background knowledge. Boosting is used for actual classification. Experimental evaluations on two well known text corpora support our approach through consistent improvement of the results.

关键词： Text categorization Boosting Ontologies data mining Tree data structures knowledge management data engineering Learning systems Information retrieval Frequency

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Iotpredictor: A Security Framework for Predicting Iot Device Behaviours and Detecting Malicious Devices Against Cyber Attacks

SSRN

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SSRN 2024年

作者： Kalaria, Rudri Kayes, A.S.M. Rahayu, Wenny Pardede, Eric Salehi, Ahmad S. La Trobe University VIC3086 Australia Data Engineering and Knowledge Management Group Australia

Securing Internet of Things (IoT) devices is paramount to mitigate unauthorised access and potential cyber threats, safeguarding the integrity of transmitted and processed data within interconnected devices. Identifying malicious IoT devices necessitates vigilant monitoring of network traffic, behaviour analysis, and implementing security measures, including Anomaly Detection Systems (ADSs), Intrusion Detection Systems (IDSs), and regular firmware updates. Traditional security approaches need to be revised for safeguarding IoT systems due to their inherent limitations in accommodating the resource-constrained nature of these *** introduce IoTPredictor, an advanced security approach designed to predict and detect malicious activities in IoT devices. Leveraging Hidden Markov Models (HMMs), IoTPredictor integrates an ADS to proactively detect and thwart attacks within the complex IoT-fog computing landscape. Our conceptual approach begins with categorising IoT devices into genuine, compromised, and counterfeit. We propose an HMM-based state transition model that captures potential transitions between states, such as normal, compromised, or counterfeit operations. We introduce an algorithm for estimating probabilities associated with next-state predictions to facilitate predictive ***, we present a formal approach for analysing communications between different states, enhancing the precision of the security framework. To validate the effectiveness of IoTPredictor, we conduct a series of experiments and provide a comprehensive evaluation. The results demonstrate the robustness and efficiency of our proposed security framework in predicting and preventing malicious activities, thereby contributing to the overall security enhancement of IoT devices within the complex IoT-fog computing network. © 2024, The Authors. All rights reserved.

关键词： Hidden Markov models

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