检索结果-内蒙古大学图书馆

Evaluating decisions: Characteristics, evaluation of outcome and serious games

学校读者我要写书评

暂无评论

Evaluating decisions: Characteristics, evaluation of outcome...

14th International Conference on Information Processing and Management of Uncertainty in knowledge-Based Systems, IPMU 2012

作者： Inthorn, Julia Haun, Stefan Hoppe, Anett Nürnberger, Andreas Dick, Michael Data and Knowledge Engineering Group Faculty of Computer Science Otto-von-Guericke-University Germany Department for Ethics and History of Medicine University Medical Center Goettingen Germany Institute for Research and Development of Collaborative Processes School of Applied Psychology University of Applied Sciences and Arts Northwestern Switzerland Switzerland

ISBN: (纸本)9783642317149

The characteristics of decisions and the evaluation of their outcome are highly complex. In this paper, we first give a short analysis of different types of decisions such as long-term and short-term decisions or dilemmas by discussing different scenarios and examples. We identify characteristics of decisions and give a short account of the usually quite complex decision scenarios involved and the high uncertainty of long-term predictions. We introduce serious games as a tool for evaluation of decisions through simulation. By using serious games long-term effects of decisions can be evaluated and known measurement criteria for short-term decision can be transformed to support long-term decisions. © 2012 Springer-Verlag Berlin Heidelberg.

关键词： Information management

Mining social media to inform peatland fire and haze disaster management

学校读者我要写书评

暂无评论

arXiv 2017年

作者： Kibanov, Mark Stumme, Gerd Amin, Imaduddin Lee, Jong Gun Knowledge & Data Engineering Group ITeG Research Center University of Kassel Germany Pulse Lab Jakarta UN Global Pulse United Nations

Peatland fires and haze events are disasters with national, regional, and international implications. The phenomena lead to direct damage to local assets, as well as broader economic and environmental losses. Satellite imagery is still the main and often the only available source of information for disaster management. In this article, we test the potential of social media to assist disaster management. To this end, we compare insights from two datasets: fire hotspots detected via NASA satellite imagery and almost all GPS-stamped tweets from Sumatra Island, Indonesia, posted during 2014. Sumatra Island is chosen as it regularly experiences a significant number of haze events, which affect citizens in Indonesia as well as in nearby countries including Malaysia and Singapore. We analyse temporal correlations between the datasets and their geo-spatial interdependence. Furthermore, we show how Twitter data reveals changes in users’ behavior during severe haze events. Overall, we demonstrate that social media are a valuable source of complementary and supplementary information for haze disaster management. Based on our methodology and findings, an analytics tool to improve peatland fire and haze disaster management by the Indonesian authorities is under development. Copyright © 2017, The Authors. All rights reserved.

关键词： Wetlands

学校读者我要写书评

暂无评论

Clones in graphs

arXiv 2018年

作者： Doerfel, Stephan Hanika, Tom Stumme, Gerd Micromata GmbH Kassel Germany Knowledge Data Engineering Group University of Kassel Interdisciplinary Research Center for Information System Design University of Kassel

Finding structural similarities in graph data, like social net-works, is a far-ranging task in data mining and knowledge discovery. A (conceptually) simple reduction would be to compute the automorphism group of a graph. However, this approach is ineffective in data mining since real world data does not exhibit enough structural regularity. Here we step in with a novel approach based on mappings that preserve the maximal cliques. For this we exploit the well known correspondence be-tween bipartite graphs and the data structure formal context (G,M, I) from Formal Concept Analysis. From there we utilize the notion of clone items. The investigation of these is still an open problem to which we add new insights with this work. Furthermore, we produce a substantial exper-imental investigation of real world *** conclude with demonstrating the generalization of clone items to *** Codes 03G10 91D30 Copyright © 2018, The Authors. All rights reserved.

关键词： Cloning

Distances for WiFi based topological indoor mapping

学校读者我要写书评

暂无评论

arXiv 2018年

作者： Schaefermeier, Bastian Hanika, Tom Stumme, Gerd L3S Research Center Leibniz University Hannover Germany Knowledge and Data Engineering Group University of Kassel Kassel Germany

For localization and mapping of indoor environments through WiFi signals, locations are often represented as likelihoods of the received signal strength indicator. In this work we compare various measures of distance between such likelihoods in combination with different methods for estimation and representation. In particular, we show that among the considered distance measures the Earth Mover's Distance seems the most beneficial for the localization task. Combined with kernel density estimation we were able to retain the topological structure of rooms in a real-world office scenario. Copyright © 2018, The Authors. All rights reserved.

关键词： Machine learning

Organizing publications and bookmarks in BibSonomy

学校读者我要写书评

暂无评论

Organizing publications and bookmarks in BibSonomy

Workshop on Social and Collaborative Construction of Structured knowledge, CKC 2007 - At the 16th International World Wide Web Conference, WWW 2007

作者： Jäschke, Robert Hotho, Andreas Schmitz, Christoph Grahl, Miranda Krause, Beate Stumme, Gerd Knowledge and Data Engineering Group Dept. of Mathematics and Computer Science Univ. of Kassel Wilhelmshöher Allee 73 D-34121 Kassel Germany Research Center L3S Univ. of Hannover Appelstr. 9a D-30167 Hannover Germany

BibSonomy is a web-based social resource sharing system which allows users to organise and share bookmarks and publications in a collaborative manner. Apart from standard folksonomy features such as an intuitive user interface, navigation along all dimensions, or browser integration via RSS feeds, BibSonomy provides tag hierarchies, group management and privacy features, and numerous import and export functions.

关键词： User interfaces

Formation and temporal evolution of social groups during coffee breaks 1

学校读者我要写书评

暂无评论

5th International Workshop on Mining Ubiquitous and Social Environments, MUSE 2014

作者： Atzmueller, Martin Ernst, Andreas Krebs, Friedrich Scholz, Christoph Stumme, Gerd Knowledge and Data Engineering Group Research Center for Information System Design University of Kassel Wilhelmshöher Allee 73 Kassel34121 Germany Center for Environmental Systems Research University of Kassel Wilhelmshöher Allee 47 Kassel34117 Germany Department Energy Informatics and Information Systems Fraunhofer Institute for Wind Energy and Energy System Technology Königstor 59 Kassel34119 Germany

ISBN: (数字)9783319290096

ISBN: (纸本)9783319290089

Group formation and evolution are prominent topics in social contexts. This paper focuses on the analysis of group evolution events in networks of face-to-face proximity. We first analyze statistical properties of group evolution, e.g., individual activity and typical group sizes. After that, we define a set of specific group evolution events. These are analyzed in the context of an academic conference, where we provide different patterns according to phases of the conference. Specifically, we investigate group formation and evolution using real-world data collected at the LWA 2010 conference utilizing the Conferator system, and discuss patterns according to different phases of the conference. © Springer International Publishing Switzerland 2016.

关键词： Computers

A Review-aware Graph Contrastive Learning Framework for Recommendation

学校读者我要写书评

暂无评论

arXiv 2022年

作者： Shuai, Jie Sun, Peijie Zhang, Kun Hong, Richang Li, Yong Wu, Le Wang, Meng Key Laboratory of Knowledge Engineering with Big Data Hefei University of Technology China Key Laboratory of Knowledge Engineering with Big Data Hefei University of Technology Institute of Artificial Intelligence Hefei Comprehensive National Science Center China Beijing National Research Center for Information Science and Technology Department of Electronic Engineering Tsinghua University China

Most modern recommender systems predict users’ preferences with two components: user and item embedding learning, followed by the user-item interaction modeling. By utilizing the auxiliary review information accompanied with user ratings, many of the existing review-based recommendation models enriched user/item embedding learning ability with historical reviews or better modeled user-item interactions with the help of available user-item target reviews. Though significant progress has been made, we argue that current solutions for review-based recommendation suffer from two drawbacks. First, as review-based recommendation can be naturally formed as a user-item bipartite graph with edge features from corresponding user-item reviews, how to better exploit this unique graph structure for recommendation? Second, while most current models suffer from limited user behaviors, can we exploit the unique self-supervised signals in the review-aware graph to guide two recommendation components better? To this end, in this paper, we propose a novel Review-aware Graph Contrastive Learning (RGCL) framework for review-based recommendation. Specifically, we first construct a review-aware user-item graph with feature-enhanced edges from reviews, where each edge feature is composed of both the user-item rating and the corresponding review semantics. This graph with feature-enhanced edges can help attentively learn each neighbor node weight for user and item representation learning. After that, we design two additional contrastive learning tasks (i.e., Node Discrimination and Edge Discrimination) to provide self-supervised signals for the two components in recommendation process. Finally, extensive experiments over five benchmark datasets demonstrate the superiority of our proposed RGCL compared to the state-of-the-art baselines. Copyright © 2022, The Authors. All rights reserved.

关键词： Recommender systems

Factorizing Lattices by Interval Relations

学校读者我要写书评

暂无评论

arXiv 2022年

作者： Koyda, Maren Stumme, Gerd Knowledge and Data Engineering Group Research Center for Information System Design University of Kassel Wilhelmshöher Allee 73 KasselD-34121 Germany

This work investigates the factorization of finite lattices to implode selected intervals while preserving the remaining order structure. We examine how complete congruence relations and complete tolerance relations can be utilized for this purpose and answer the question of finding the finest of those relations to implode a given interval in the generated factor lattice. To overcome the limitations of the factorization based on those relations, we introduce a new lattice factorization that enables the imploding of selected disjoint intervals of a finite lattice. To this end, we propose an interval relation that generates this factorization. To obtain lattices rather than arbitrary ordered sets, we restrict this approach to so-called pure intervals. For our study, we will make use of methods from Formal Concept Analysis (FCA). We will also provide a new FCA construction by introducing the enrichment of an incidence relation by a set of intervals in a formal context, to investigate the approach for lattice-generating interval relations on the context *** Codes 06B05, 06B10, 68R01 Copyright © 2022, The Authors. All rights reserved.

关键词： Formal concept analysis

学校读者我要写书评

暂无评论

Scaling Dimension

arXiv 2023年

作者： Ganter, Bernhard Hanika, Tom Hirth, Johannes TU Dresden Dresden Germany Knowledge & Data Engineering Group University of Kassel Germany Interdisciplinary Research Center for Information System Design University of Kassel Germany

Conceptual Scaling is a useful standard tool in Formal Concept Analysis and beyond. Its mathematical theory, as elaborated in the last chapter of the FCA monograph, still has room for improvement. As it stands, even some of the basic definitions are in flux. Our contribution was triggered by the study of concept lattices for tree classifiers and the scaling methods used there. We extend some basic notions, give precise mathematical definitions for them and introduce the concept of scaling dimension. In addition to a detailed discussion of its properties, including an example, we show theoretical bounds related to the order dimension of concept lattices. We also study special subclasses, such as the ordinal and the interordinal scaling dimensions, and show for them first results and *** Codes 03G10 68T27 68T30 06B10 06A15 Copyright © 2023, The Authors. All rights reserved.

关键词： Formal concept analysis