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2011 IEEE International Conference on Privacy, Security, Risk and Trust, PASSAT 2011 and 2011 IEEE International Conference on Social Computing, SocialCom 2011

作者： Lemmerich, Florian Atzmueller, Martin Artificial Intelligence and Applied Computer Science University of Würzburg 97074 Ẅurzburg Germany Knowledge and Data Engineering Group University of Kassel 34121 Kassel Germany

ISBN: (纸本)9780769545783

This paper presents an approach for modeling location-based profiles of social image media based on tagging information and collaborative geo-reference annotations. We utilize pattern mining techniques for obtaining sets of tags that are specific for the specified point, landmark, or region of interest. Next, we show how these candidate patterns can be presented and visualized for interactive exploration using a combination of general pattern mining visualizations and views specialized on geo-referenced tagging data. We present a case study using publicly available data from the Flickr photo sharing application. © 2011 IEEE.

关键词： data mining

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Assessing the quality of R2RML mappings 1

Assessing the quality of R2RML mappings

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Joint 1st International Workshop on Semantics for Transport and the 1st International Workshop on Approaches for Making data Interoperable, SEM4TRA-AMAR 2019

作者： Crotti, Ademar Debattista, Jeremy O’Sullivan, Declan ADAPT Centre for Digital Content Platform Research Knowledge and Data Engineering Group School of Computer Science and Statistics Trinity College Dublin Dublin 2 Ireland

This paper presents an approach to assess the quality of mappings used to generate RDF datasets. data quality is a multidimensional concept determined by many factors which influence the extent by which a dataset is useful for a particular task. Several solutions have been proposed in literature to assess the quality of RDF datasets. Nonetheless, in most cases, these solutions focus on the resulting datasets and not on the artefacts used to generate these. In this paper, we propose the use of metrics commonly used to assess the quality of such datasets to evaluate the mappings used to generate them. The goal is to assist data providers into producing high quality datasets by bringing such quality assessment procedures to also cover the start of the publishing process. We provide an implementation of the approach by extending an existing quality assessment framework, which is then evaluated using real world use cases. Preliminary results shows that the assessment of mappings is capable to identifying quality issues for the observed cases. Copyright © 2019 for this paper by its authors. Use permitted under Creative Commons License Attribution 4.0 International (CC BY 4.0).

关键词： Mapping

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Semantic Web mining and the representation, analysis, and evolution of Web space

Semantic Web mining and the representation, analysis, and ev...

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International Workshop on Representation and Analysis of Web Space, RAWS 2005

作者： Berendt, Bettina Hotho, Andreas Stumme, Gerd Institute of Information Systems Humboldt University Berlin 10 78 Berlin Germany Knowledge and Data Engineering Group University of Kassel D-34121 Kassel Germany

Semantic Web Mining aims at combining the two fast-developing research areas Semantic Web and Web Mining. This survey analyzes the convergence of trends from both areas: Growing numbers of researchers work on improving the results of Web Mining by exploiting semantic structures in the Web, and they use Web Mining techniques for building the Semantic Web. Last but not least, these techniques can be used for mining the Semantic Web itself. The second aim of this paper is to use these concepts to circumscribe what Web space is, what it represents and how it can be represented and analyzed. This is used to sketch the role that Semantic Web Mining and the software agents and human agents involved in it can play in the evolution of Web space.

关键词： Semantic Web

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VIKAMINE - Open-source subgroup discovery, pattern mining, and analytics

VIKAMINE - Open-source subgroup discovery, pattern mining, a...

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2012 European Conference on Machine Learning and Principles and Practice of knowledge Discovery in databases, ECML-PKDD 2012

作者： Atzmueller, Martin Lemmerich, Florian University of Kassel Knowledge and Data Engineering Group Wilhelmshöher Allee 73 34121 Kassel Germany University of Wuerzburg Artificial Intelligence and Applied Informatics Group Am Hubland Wuerzburg 97074 Germany

ISBN: (纸本)9783642334856

This paper presents an overview on the VIKAMINE system for subgroup discovery, pattern mining and analytics. As of VIKAMINE version 2, it is implemented as rich-client platform (RCP) application, based on the Eclipse framework. This provides for a highly-configurable environment, and allows modular extensions using plugins. We present the system, briefly discuss exemplary plugins, and provide a sketch of successful applications. © 2012 Springer-Verlag.

关键词： data mining

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On Aggregation in Ensembles of Multilabel Classifiers 23rd

On Aggregation in Ensembles of Multilabel Classifiers

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23rd International Conference on Discovery Science, DS 2020

作者： Nguyen, Vu-Linh Hüllermeier, Eyke Rapp, Michael Loza Mencía, Eneldo Fürnkranz, Johannes Heinz Nixdorf Institute and Department of Computer Science Paderborn University Paderborn Germany Knowledge Engineering Group TU Darmstadt Darmstadt Germany Computational Data Analytics Group JKU Linz Linz Austria

ISBN: (纸本)9783030615260

While a variety of ensemble methods for multilabel classification have been proposed in the literature, the question of how to aggregate the predictions of the individual members of the ensemble has received little attention so far. In this paper, we introduce a formal framework of ensemble multilabel classification, in which we distinguish two principal approaches: "predict then combine" (PTC), where the ensemble members first make loss minimizing predictions which are subsequently combined, and "combine then predict" (CTP), which first aggregates information such as marginal label probabilities from the individual ensemble members, and then derives a prediction from this aggregation. While both approaches generalize voting techniques commonly used for multilabel ensembles, they allow to explicitly take the target performance measure into account. Therefore, concrete instantiations of CTP and PTC can be tailored to concrete loss functions. Experimentally, we show that standard voting techniques are indeed outperformed by suitable instantiations of CTP and PTC, and provide some evidence that CTP performs well for decomposable loss functions, whereas PTC is the better choice for non-decomposable losses. © 2020, Springer Nature Switzerland AG.

关键词： Forecasting

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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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Enhancing Playout Policy Adaptation for General Game Playing 1

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1st Workshop on Monte Carlo Search, MCS 2020, Held in conjunction with IJCAI 2020

作者： Sironi, Chiara F. Cazenave, Tristan Winands, Mark H. M. Game AI & Search Group Department of Data Science and Knowledge Engineering Maastricht University Maastricht Netherlands LAMSADE Université Paris-Dauphine PSL CNRS Paris France

ISBN: (数字)9783030894535

ISBN: (纸本)9783030894528

Playout Policy Adaptation (PPA) is a state-of-the-art strategy that has been proposed to control the playouts in Monte-Carlo Tree Search (MCTS). PPA has been successfully applied to many two-player, sequential-move games. This paper further evaluates this strategy in General Game Playing (GGP) by first reformulating it for simultaneous-move games. Next, it presents five enhancements for the strategy, four of which have been previously successfully applied to a related MCTS playout strategy, the Move-Average Sampling Technique (MAST). Experiments on a heterogeneous set of games show three enhancements to have a positive effect on PPA: (i) updating the policy for all players proportionally to their payoffs instead of updating only the policy of the winner, (ii) collecting statistics for N-grams of moves instead of single moves only, and (iii) discounting the backpropagated payoffs depending on the depth of the playout. Results also show enhanced PPA variants to be competitive with MAST for small search budgets, and better for larger search budgets. The use of an ϵ -greedy selection of moves and of after-move decay of statistics, instead, seem to have a detrimental effect on PPA. © 2021, Springer Nature Switzerland AG.

关键词： Monte Carlo methods

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An Amharic Syllable-Based Speech Corpus for Continuous Speech Recognition 1

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7th International Conference on Statistical Language and Speech Processing, SLSP 2019

作者： Gebreegziabher, Nirayo Hailu Nürnberger, Andreas Fakultät für Informatik Data and Knowledge Engineering Group Otto von Guericke Universität Magdeburg Universitätsplatz 2 Magdeburg39106 Germany

ISBN: (数字)9783030313722

ISBN: (纸本)9783030313715

Speech recognition systems play an important role in solving problems such as spoken content retrieval. Thus, we are interested in the task of speech recognition for low-resource languages, such as Amharic. The main challenges in solving Amharic speech recognition are the limited availability of corpora and complex morphological nature of the language. This paper presents a new corpus for the low-resource Amharic language which is suitable for training and evaluation of speech recognition systems. The corpus prepared contains 90 h of speech data with word and syllable-based annotation. Moreover, the use of syllable units for acoustic and language model in comparison with a morpheme-based model is presented. Syllable-based triphone speech recognition system provides a lower word error rate of 16.82% on the subset of the dataset. Moreover, syllable-based hybrid deep neural network with hidden Markov model provides a 14.36% word error rate. © 2019, Springer Nature Switzerland AG.

关键词： Hidden Markov models

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Managing user-centric adaptive services for pervasive computing

Managing user-centric adaptive services for pervasive comput...

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International Conference on Autonomic Computing (ICAC)

作者： D. Lewis T. O'Donnell K. Feeney A. Brady V. Wade Computer Science Department Knowledge and Data Engineering Group Dublin Ireland Knowledge and Data Engineering Group Computer Science Department Trinity College Dublin Ireland

Pervasive computing environments need to exhibit highly adaptive behavior to meet the changing task requirements and operational context of visiting mobile users. However this must be balanced with the need of resource owners to meet their goals in administering how users use their resources. This presents challenges of how to manage adaptive systems and how such management should be exercised by people, both average pervasive computing users and administrators of pervasive computing resources. This paper presents some of the issues involved in reconciling dynamic user-centric adaptation with the management of autonomic systems to meet high-level management policies. It discusses our architectural approach and presents some initial research results in addressing these issues.

关键词： Pervasive computing Resource management Programmable control Adaptive control Personal digital assistants data engineering Computer science Educational institutions Mobile computing Adaptive systems

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Event-based clustering for reducing labeling costs of incident-related microposts 2

Event-based clustering for reducing labeling costs of incide...

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2nd International Workshop on Mining Urban data, MUD 2015 - co-located with 32nd International Conference on Machine Learning, ICML 2015

作者： Schulz, Axel Ristoski, Petar Fürnkranz, Johannes Janssen, Frederik DB Mobility Logistics AG Telecooperation Lab Technische Universität Darmstadt Germany Data and Web Science Group University of Mannheim Germany Knowledge Engineering Group Technische Universität Darmstadt Germany

Automatically identifying the event type of event-related information in the sheer amount of social media data makes machine learning inevitable. However, this is highly dependent on (1) the number of correctly labeled instances and (2) labeling costs. Active learning has been proposed to reduce the number of instances to label. Though, current approaches focus on the thematic dimension, i.e., the event type, for selecting instances to label;other metadata such as spatial and temporal information that is helpful for achieving a more fine-grained clustering is currently not taken into account. Also, labeling quality is always assumed to be perfect as currently no qualitative information is present for manual event type labeling. In this paper, we present a novel event-based clustering strategy that makes use of temporal, spatial, and thematic metadata to determine instances to label. Furthermore, we also inspect the quality of the manual labeling in a crowdsourcing study by comparing experts and non-experts. An evaluation on incident-related tweets shows that (i) labels provided by crowdsourcing are of acceptable quality and (ii) our selection strategy for active learning outperforms current state-of-theart approaches even with few labeled instances. Copyright © 2015 for this paper by its authors.

关键词： Metadata

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