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23rd International Conference of the Italian Association for Artificial Intelligence, AIxIA 2024

作者： Chatterjee, Soumick Xu, Jiahua Kuzhipathalil, Adarsh Nürnberger, Andreas Faculty of Computer Science Otto von Guericke University Magdeburg Magdeburg Germany Data and Knowledge Engineering Group Otto von Guericke University Magdeburg Magdeburg Germany Genomics Research Centre Human Technopole Milan Italy Hertie Institute for Clinical Brain Research Tuebingen Germany XenomatiX NV Leuven Belgium

ISBN: (纸本)9783031806063

In recent years, the field of autonomous vehicles and driverless technology has seen remarkable advancements, driven by contributions from mainstream automotive manufacturers and open-source projects. This research aims to develop a pipeline for road scene understanding through semantic segmentation. The proposed pipeline utilises a multi-modal segmentation model, incorporating greyscale images and point cloud data from Xenolidar, specifically designed to capture the structural priors of highway road scenes. The fusion of input modalities and the design of an encoder-decoder architecture with a novel attention scheme called HaWANet is introduced, which focuses on the height and width contextual information to improve the accuracy of road segmentation, are the primary aspects explored for the proposed model. The output of the encoder is a two-dimensional point cloud, which effectively represents the road’s planar nature, and is crucial for improving the accuracy of road segmentation, particularly in edge cases, addressing current challenges in autonomous driving research. This research, aimed at addressing the segmentation problem for multimodal sensor data, has presented significant performance improvement over single-modal approaches. © The Author(s), under exclusive license to Springer Nature Switzerland AG 2025.

关键词： Semantic Segmentation

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Exploring Heterogeneity and Uncertainty for Graph-based Cognitive Diagnosis Models in Intelligent Education 25

Exploring Heterogeneity and Uncertainty for Graph-based Cogn...

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Proceedings of the 31st ACM SIGKDD Conference on knowledge Discovery and data Mining V.1

作者： Pengyang Shao Yonghui Yang Chen Gao Lei Chen Kun Zhang Chenyi Zhuang Le Wu Yong Li Meng Wang Key Laboratory of Knowledge Engineering with Big Data Hefei University of Technology Hefei Anhui China BNRist Tsinghua University Beijing China Department of Electronic Engineering BNRist Tsinghua University Beijing China Ant Group HangZhou Zhejiang China

ISBN: (纸本)9798400712456

Graph-based Cognitive Diagnosis (CD) has attracted much research interest due to its strong ability on inferring students' proficiency levels on knowledge concepts. While graph-based CD models have demonstrated remarkable performance, we contend that they still cannot achieve optimal performance due to the neglect of edge heterogeneity and uncertainty. Edges involve both correct and incorrect response logs, indicating heterogeneity. Meanwhile, a response log can have uncertain semantic meanings, e.g., a correct log can indicate true mastery or fortunate guessing, and a wrong log can indicate a lack of understanding or a careless mistake. In this paper, we propose an Informative Semantic-aware Graph-based Cognitive Diagnosis model (ISG-CD), which focuses on how to utilize the heterogeneous graph in CD and minimize effects of uncertain edges. Specifically, to explore heterogeneity, we propose a semantic-aware graph neural networks based CD model. To minimize effects of edge uncertainty, we propose an Informative Edge Differentiation layer from an information bottleneck perspective, which suggests keeping a minimal yet sufficient reliable graph for CD in an unsupervised way. We formulate this process as maximizing mutual information between the reliable graph and response logs, while minimizing mutual information between the reliable graph and the original graph. After that, we prove that mutual information maximization can be theoretically converted to the classic binary cross entropy loss function, while minimizing mutual information can be realized by the Hilbert-Schmidt Independence ***, we adopt an alternating training strategy for optimizing learnable parameters of both the semantic-aware graph neural networks based CD model and the edge differentiation layer. Extensive experiments on three real-world datasets have demonstrated the effectiveness of ISG-CD.

关键词： cognitive diagnosis

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Temporal evolution of contacts and communities in networks of face-to-face human interactions

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Science China(Information Sciences) 2014年第3期57卷 29-45页

作者： Mark KIBANOV Martin ATZMUELLER Christoph SCHOLZ Gerd STUMME Knowledge and Data Engineering Group University of KasselWilhelmshher Allee 73Kassel D-34121Germany

Temporal dynamics of social interaction networks as well as the analysis of communities are key aspects to gain a better understanding of the involved processes,important influence factors,their efects,and their structural *** this article,we analyze temporal dynamics of contacts and the evolution of communities in networks of face-to-face *** our application context,we consider four scientific *** a structural level,we focus on static and dynamic properties of the contact ***,we analyze the resulting community structure using state-of-the-art automatic community detection ***,we analyze the evolution of contacts and communities over time to consider the stability of the respective ***,we assess diferent factors which have an influence on the quality of community ***,we provide first important insights into the evolution of contacts and communities in face-to-face contact networks.

关键词： social network analysis community detection face-to-face contact networks temporal networks community stability

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INTEGRATING knowledge-BASED SYSTEMS AND dataBASES

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CLINICA CHIMICA ACTA 1993年第1-2期222卷 101-115页

作者： GRIMSON, JB Knowledge and Data Engineering Group Department of Computer Science Trinity College Dublin 2 Ireland

In recent years, there has been an explosion of interest among the computing community in the field of artificial intelligence, particularly in the areas of natural language processing and knowledge-based systems (KBS). The medical domain has seen the development of hundreds of KBSs and there is substantial evidence to show that the application of a knowledge-based approach to decision support can go a long way towards overcoming the information overload experienced by many clinicians today. Yet many of these medical KBSs are still at the prototype stage and are mainly confined to research laboratories. There are many reasons for this apparently slow take-up of the technology, but one of the most significant is the lack of integration into the regular routine information processing of the organisation, in particular the database processing. This paper discusses the benefits of such integration and methods for achieving it in the context of general trends in information systems. database technology provides efficient and secure management of large amounts of data in a multi-user, multiapplication environment. knowledge-based technology, on the other hand, provides mechanisms for building intelligent systems. Thus, for example, given a set of facts about a domain (symptoms, laboratory test results, etc.) together with a set of rules which apply to that domain (e.g.'if TT4 > 150 nmol/l then suspect hyperthyroidism'), a KBS can deduce new information about that domain automatically. The effective integration of these two technologies is seen as a means of achieving the intelligent information systems of the future. There are three basic approaches to integrating KBSs and databases. The first is to start with the KBS and incorporate data management functions. Alternatively, intelligence from the KBS can be incorporated into the database. Finally, the two systems can be allowed to coexist as independent systems which can talk to each other by means of standard interfaces.

关键词： dataBASE MANAGEMENT knowledge-BASED SYSTEMS EXPERT SYSTEMS

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Towards the Technology Neutral Modeling of Management Components

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Journal of Network and Systems Management 2003年第1期11卷 39-56页

作者： Lewis, David Wade, Vincent Cullen, Brian Knowledge and Data Engineering Group Department of Computer Science Trinity College Dublin Dublin 2 Ireland

This paper outlines an Architectural Model and accompanying modeling notation that addresses on the need to model management component interfaces and their business contexts in a technology neutral manner in order to promote convergence on stable, reusable solutions. The approach combines existing modeling concepts related to component-based and model-driven software development from TINA-C, OMG, DMTF and TM Forum in order to provide guidance on the development of models that need to be exchanged between organizations involved in the development of software components and the management systems in which they are used. The Architectural Model is assessed through application to the management a specific set of e-business support services.

关键词： Electronic commerce

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Integrating the policy dialectic into dynamic spectrum management

Integrating the policy dialectic into dynamic spectrum manag...

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2nd IEEE International Symposium on New Frontiers in Dynamic Spectrum Access Networks

作者： Lewis, David Feeney, Kevin O'Sullivan, Declan Knowledge and Data Engineering Group Department of Computer Science and Statistics Ireland CTVR Ireland Knowledge and Data Engineering Group (KDEG) Department of Computer Science and Statistics TCD Ireland

ISBN: (纸本)9781424406623

In this paper we propose a holistic approach to modeling the management of dynamic spectrum access (DSA). We argue that the range to issues involved requires not just a management scheme, but also a meta-management scheme whereby management processes are monitored, analyzed and improved. In this way different proposals for management can be refined through interaction in a dialectic that reacts to the problems and conflicts of a given management scheme as well as the changes in the technological, social, economic and political environment. We examine Stafford Beer's Viable Systems Model as a possible basis for a framework that encompasses a variety of feedback loops involved in addressing operations, management and meta-management together. We also propose how this model could be mapped onto a concrete policy meta-management system and sketch out issues worthy of further investigation in developing a holistic DSA management framework.

关键词： Metadata

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The anti-social tagger - Detecting spam in social bookmarking systems

The anti-social tagger - Detecting spam in social bookmarkin...

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4th International Workshop on Adversarial Information Retrieval on the Web, AIRWeb 2008

作者： Krause, Beate Hotho, Andreas Schmitz, Christoph Stumme, Gerd Knowledge and Data Engineering Group University of Kassel Germany

ISBN: (纸本)9781605581590

The annotation of web sites in social bookmarking systems has become a popular way to manage and find information on the web. The community structure of such systems attracts spammers: recent post pages, popular pages or specific tag pages can be manipulated easily. As a result, searching or tracking recent posts does not deliver quality results annotated in the community, but rather unsolicited, often commercial, web sites. To retain the benefits of sharing one's web content, spam-fighting mechanisms that can face the flexible strategies of spammers need to be developed. A classical approach in machine learning is to determine relevant features that describe the system's users, train different classifiers with the selected features and choose the one with the most promising evaluation results. In this paper we will transfer this approach to a, social bookmarking setting to identify spammers. We will present features considering the topological, semantic and profile-based information which people make public when using the system. The dataset used is a snapshot of the social bookmarking system BibSonomy and was built over the course of several months when cleaning the system from spam. Based on our features, we will learn a large set of different classification models and compare their performance. Our results represent the groundwork for a first application in BibSonomy and for the building of more elaborate spam detection mechanisms.

关键词： Semantics

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Unsupervised and hybrid approaches for on-line RFID localization with mixed context knowledge

Unsupervised and hybrid approaches for on-line RFID localiza...

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21st International Symposium on Methodologies for Intelligent Systems, ISMIS 2014

作者： Scholz, Christoph Atzmueller, Martin Stumme, Gerd Knowledge and Data Engineering Group University of Kassel Germany

ISBN: (纸本)9783319083254

Indoor localization of humans is still a complex problem, especially in resource-constrained environments, e. g., if there is only a small number of data available over time. We address this problem using active RFID technology and focus on room-level localization. We propose several unsupervised localization approaches and compare their accuracy to state-of-the art unsupervised and supervised localization methods. In addition, we combine unsupervised and supervised methods into a hybrid approach using different types of mixed context knowledge. We show, that the new unsupervised approaches significantly outperform state-of-the-art supervised methods, and that the hybrid approach performs best in our application setting. We analyze real world data collected at a two days evaluation of our working group management system Mygroup. © 2014 Springer International Publishing.

关键词： Information management

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Conexp-Clj – A research tool for FCA 15

Conexp-Clj – A research tool for FCA

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15th Supplementary International Conference on Formal Concept Analysis Workshops, ICFCA 2019

作者： Hanika, Tom Hirth, Johannes Knowledge and Data Engineering Group University of Kassel Germany

There is a plenitude of software programs to analyze data sets using notions from formal concept analysis (FCA). For example, there are 64 FCA related projects listed on GitHub. Those are developed in ten different programming languages and provide tools and libraries for computing formal concepts and alike. The research tool conexp-clj sticks out in this list. It is the only application in the FCA realm developed using the programming language Clojure, which is a modern, dynamic, and functional dialect of the Lisp programming language running on the Java platform. We summarize in this work the extensive set of notions from FCA that are covered by conexp-clj, show recent developments, present simple examples on a real world data set and depict a timeline for our next goals. Copyright © 2019 for this paper by its authors.

关键词： Functional programming

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How to select a suitable tool for a software development project: Three case studies and the lessons learned

How to select a suitable tool for a software development pro...

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Multi-Conference on Software engineering, SE 2013

作者： Kibanov, Mark Erdmann, Dominik J. Atzmueller, Martin Knowledge and Data Engineering Group University of Kassel Germany

ISBN: (纸本)9783885796091

This paper describes a framework for evaluating and selecting suitable software tools for a software project, which is easily extendable depending on needs of the project. For an evaluation, we applied the presented framework in three different projects. These projects use different software development methods (from classical models to Scrum) in different environments (industry and academia). We discuss our experiences and the lessons learned. © Gesellschaft für Informatik, Bonn 2013.

关键词： Computer aided software engineering

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