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16th International Conference on Formal Concept Analysis, ICFCA 2021

作者： Dürrschnabel, Dominik Stumme, Gerd Knowledge and Data Engineering Group University of Kassel Kassel Germany Interdisciplinary Research Center for Information System Design University of Kassel Kassel Germany

ISBN: (纸本)9783030778668

Order diagrams allow human analysts to understand and analyze structural properties of ordered data. While an expert can create easily readable order diagrams, the automatic generation of those remains a hard task. In this work, we adapt force-directed approaches, which are known to generate aesthetically-pleasing drawings of graphs, to the realm of order diagrams. Our algorithm ReDraw thereby embeds the order in a high dimension and then iteratively reduces the dimension until a two-dimensional drawing is achieved. To improve aesthetics, this reduction is equipped with two force-directed steps where one step optimizes the distances of nodes and the other one the distances of lines in order to satisfy a set of a priori fixed conditions. By respecting an invariant about the vertical position of the elements in each step of our algorithm we ensure that the resulting drawings satisfy all necessary properties of order diagrams. Finally, we present the results of a user study to demonstrate that our algorithm outperforms comparable approaches on drawings of lattices with a high degree of distributivity. © 2021, Springer Nature Switzerland AG.

关键词： Iterative methods

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Towards explainable scientific venue recommendations

arXiv

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arXiv 2021年

作者： Schaefermeier, Bastian Stumme, Gerd Hanika, Tom Knowledge and Data Engineering Group University of Kassel

Selecting the best scientific venue (i.e., conference/journal) for the submission of a research article constitutes a multifaceted challenge. Important aspects to consider are the suitability of research topics, a venue's prestige, and the probability of acceptance. The selection problem is exacerbated through the continuous emergence of additional venues. Previously proposed approaches for supporting authors in this process rely on complex recommender systems, e.g., based on Word2Vec or TextCNN. These, however, often elude an explanation for their recommendations. In this work, we propose an unsophisticated method that advances the state-of-the-art in two aspects: First, we enhance the interpretability of recommendations through non-negative matrix factorization based topic models;Second, we surprisingly can obtain competitive recommendation performance while using simpler learning methods. Copyright © 2021, The Authors. All rights reserved.

关键词： Recommender systems

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New insights and methods for predicting face-to-face contacts

New insights and methods for predicting face-to-face contact...

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7th International AAAI Conference on Weblogs and Social Media, ICWSM 2013

作者： Scholz, Christoph Atzmueller, Martin Stumme, Gerd Barrat, Alain Cattuto, Ciro Knowledge and Data Engineering Group University of Kassel Germany Centre de Physique Théorique CNRS UMR 6207 Marseille France Data Science Laboratory ISI Foundation Torino Italy

ISBN: (纸本)9781577356103

The prediction of new links in social networks is a challenging task. In this paper, we focus on predicting links in networks of face-to-face spatial proximity by using information from online social networks, such as co-authorship networks in DBLP, and a number of node level attributes. First, we analyze influence factors for the link prediction task. Then, we propose a novel method that combines information from different networks and node level attributes for the prediction task: We introduce an unsupervised link prediction method based on rooted random walks, and show that it outperforms state-of-the-art unsupervised link prediction methods. We present an evaluation using three real-world datasets. Furthermore, we discuss the impact of our results and of the insights we glean in the field of link prediction and human contact behavior. Copyright © 2013, Association for the Advancement of Artificial Intelligence (***). All rights reserved.

关键词： Social networking (online)

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Generic pattern trees for exhaustive exceptional model mining

Generic pattern trees for exhaustive exceptional model minin...

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

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

ISBN: (纸本)9783642334856

Exceptional model mining has been proposed as a variant of subgroup discovery especially focusing on complex target concepts. Currently, efficient mining algorithms are limited to heuristic (non exhaustive) methods. In this paper, we propose a novel approach for fast exhaustive exceptional model mining: We introduce the concept of valuation bases as an intermediate condensed data representation, and present the general GP-growth algorithm based on FP-growth. Furthermore, we discuss the scope of the proposed approach by drawing an analogy to data stream mining and provide examples for several different model classes. Runtime experiments show improvements of more than an order of magnitude in comparison to a naive exhaustive depth-first search. © 2012 Springer-Verlag.

关键词： Heuristic algorithms

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Describing locations using tags and images: Explorative pattern mining in social media

Describing locations using tags and images: Explorative patt...

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2nd International Workshop on Modeling and Mining Ubiquitous Social Media, MSM 2011, MUSE 2011

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

ISBN: (纸本)9783642336836

This paper presents an approach for explorative pattern mining in social 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 platform. © 2012 Springer-Verlag.

关键词： data mining

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Voice-activated user interfaces to search for young users 43

Voice-activated user interfaces to search for young users

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43. Jahrestagung der Gesellschaft fur Informatik e.V. ,GI, Informatik Angepasst an Mensch, Organisation und Umwelt, Informatik 2013 - 43rd Annual Meeting of the German Informatics Society (GI), Computer Science Adapting to Individuals, Organizations and Environment, Informatics 2013

作者： Gossen, Tatiana Kotzyba, Michael Stober, Sebastian Nürnberger, Andreas Data & Knowledge Engineering Group Fakultät für Informatik Otto-von-Guericke-Universität Magdeburg MagdeburgD-39106 Germany

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A systematic comparison of music similarity adaptation approaches

A systematic comparison of music similarity adaptation appro...

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13th International Society for Music Information Retrieval Conference, ISMIR 2012

作者： Wolff, Daniel Weyde, Tillman Stober, Sebastian Nürnberger, Andreas MIRG School of Informatics City University London United Kingdom Data and Knowledge Engineering Group Otto-von-Guericke-Universität Magdeburg Germany

ISBN: (纸本)9789727521449

In order to support individual user perspectives and different retrieval tasks, music similarity can no longer be considered as a static element of Music Information Retrieval (MIR) systems. Various approaches have been proposed recently that allow dynamic adaptation of music similarity measures. This paper provides a systematic comparison of algorithms for metric learning and higher-level facet distance weighting on the MagnaTagATune dataset. A cross-validation variant taking into account clip availability is presented. Applied on user generated similarity data, its effect on adaptation performance is analyzed. Special attention is paid to the amount of training data necessary for making similarity predictions on unknown data, the number of model parameters and the amount of information available about the music itself. © 2012 International Society for Music Information Retrieval.

关键词： Search engines

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A trust model for capability delegation in federated policy systems

A trust model for capability delegation in federated policy ...

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6th International Conference on Risks and Security of Internet and Systems, CRiSIS 2011

作者： Feeney, Kevin Foley, Simon N. Brennan, Rob Intelligent Systems Lab Knowledge and Data Engineering Group Trinity College Dublin Ireland FAME Department of Computer Science University College Cork Ireland

ISBN: (纸本)9781457718915

Federated policy systems are required to support the emergent complexity and organizational heterogeneity of modern Internet service delivery. This paper presents a distributed policy management approach which utilizes a flexible, tree-based capability authority model to partition and delegate federated capabilities or services. A trust management model and a delegation logic is defined which supports secure decentralized policy reasoning and addresses performance overheads due to distributed rule evaluation, threats from malformed or malicious federated principals and allows flexibility with respect to delegation chain reduction or capability authority re-partitioning. The system is evaluated through a security analysis and a prototype implementation of a federated policy engineering framework based on this logic is described. This framework is based on public key certificates and an extension to the Keynote Trust Management language. It provides practical management services such as key discovery and certificate revocation in addition to the core capability delegation function. © 2011 IEEE.

关键词： Computer circuits

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From Clustering to Intelligent Decision Support System: An Application to 3D Printing 26

From Clustering to Intelligent Decision Support System: An A...

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26th International Conference of the Catalan Association for Artificial Intelligence, CCIA 2024

作者： Karna, Ashutosh Gibert, Karina Knowledge Engineering and Machine Learning Group Intelligent Data Science and Artificial Intelligence Research Centre Universitat Politècnica de Catalunya Barcelona Spain

ISBN: (纸本)9781643685434

This study focuses on developing an intelligent decision support system (IDSS) that helps a human operator make data-driven decisions. To put IDSS in production, it is necessary to develop two additional components: one oriented to recognize the cluster of new data and the other a knowledge-based resulting from the interpretation of clusters and further association of actions to each cluster, constituting a knowledge base with the alerts and recommendations associated to every profile. Bootstrap-CURE technique is used to handle the initial component, whereas a meta-clustering framework is suggested for interpreting the clusters and providing recommendations. A detailed strategy is presented for handling a print job, examining patterns, and executing actions through IDSS, thus improving predictive accuracy and operational efficiency. Two distinct machine learning models were developed, one to detect the operational mode and another to choose the best meta-cluster for the type of printing jobs and detained steps are provided for implementing the recommendations. © 2024 The Authors.

关键词： Printing presses

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Semantic Web Mining. State of the Art and Future Directions

SSRN

引用

SSRN 2018年

作者： Stumme, Gerd Hotho, Andreas Berendt, Bettina Knowledge & Data Engineering Group Institute of Information Systems

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: an increasing number of researchers is working on improving the results of Web Mining by exploiting semantic structures in the Web, and they make use o Web Mining techniques for building the Semantic Web. Last but not least, these techniques can be used for mining the Semantic Web itself. The Semantic Web is the second-generation WWW, enriched by machine-processable information which supports the user in his tasks. Given the enormous size even of today's Web, it is impossible to manually enrich all of these resources. Therefore, automated schemes for learning the relevant information are increasingly being used. Web Mining aims at discovering insights about the meaning of Web resources and their usage. Given the primarily syntactical nature of the data being mined, the discovery of meaning is impossible based on these data only. Therefore, formalizations of the semantics of Web sites and navigation behavior are becoming more and more common. Furthermore, mining the Semantic Web itself is another upcoming application. We argue that the two areas Web Mining and Semantic Web need each other to fulfill their goals, but that the full potential of this convergence is not yet realized. This paper gives an overview of where the two areas meet today, and sketches ways of how a closer integration could be profitable. © 2018, The Authors. All rights reserved.

关键词： data mining

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