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Formation and temporal evolution of social groups during coffee breaks 1

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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

Advances in Self-Organizing Maps, Learning Vector Quantization, Clustering and data Visualization 1

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丛书名： Advances in Intelligent Systems and Computing

1000年

作者： Alfredo Vellido Karina Gibert Cecilio Angulo José David Martín Guerrero

Dual Encoding for Zero-Example Video Retrieval

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Dual Encoding for Zero-Example Video Retrieval

IEEE/CVF Conference on Computer Vision and Pattern Recognition

作者： Jianfeng Dong Xirong Li Chaoxi Xu Shouling Ji Yuan He Gang Yang Xun Wang College of Computer and Information Engineering Zhejiang Gongshang University Key Lab of Data Engineering and Knowledge Engineering Renmin University of China AI & Media Computing Lab School of Information Renmin University of China College of Computer Science Zhejiang University Alibaba Group

ISBN: (纸本)9781728132945

This paper attacks the challenging problem of zero-example video retrieval. In such a retrieval paradigm, an end user searches for unlabeled videos by ad-hoc queries described in natural language text with no visual example provided. Given videos as sequences of frames and queries as sequences of words, an effective sequence-to-sequence cross-modal matching is required. The majority of existing methods are concept based, extracting relevant concepts from queries and videos and accordingly establishing associations between the two modalities. In contrast, this paper takes a concept-free approach, proposing a dual deep encoding network that encodes videos and queries into powerful dense representations of their own. Dual encoding is conceptually simple, practically effective and end-to-end. As experiments on three benchmarks, i.e. MSR-VTT, TRECVID 2016 and 2017 Ad-hoc Video Search show, the proposed solution establishes a new state-of-the-art for zero-example video retrieval.

关键词： Videotapes video retrieval End users end-to-end Dual coding

Towards a holistic knowledge management framework for healthcare institutions

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Towards a holistic knowledge management framework for health...

Annual International Conference of the IEEE engineering in Medicine and Biology Society (EMBC)

作者： A. Dwivedi R.K. Bali A.E. James R.N.G. Naguib D. Johnston Data and Knowledge Engineering Research Group (DKERG) School of Mathematical and Information Sciences Coventry University UK BIOCORE School of Mathematical and Information Sciences Coventry University UK Applied Network Solutions Limited UK

Despite substantial investments in information technology (IT), organizations have not been able to exploit the advantages of the Information and Communication Technology (ICT) revolution to the desired extent. This is also true for the healthcare sector. Twenty first century healthcare practitioners face the challenge of transforming large amounts of data into information, which then has to be converted into contextual knowledge. This process of knowledge creation and conversion is further accentuated as transformation of information into knowledge calls for: (1) contextual recognition of Information and (2) a mechanism to support effective transfer of knowledge. Also reinforced is the recognition that it is essential to have a framework that supports the dissemination of the contextual knowledge acquired. We argue the knowledge Management (KM) paradigm is aptly suited for this purpose. However, the lack of an explicit and generic framework for adopting KM has hindered its rapid acceptance in the healthcare sector. Using data inputs from a collaborating organization, we then present the Organization Current knowledge Design (OCKD) model - a holistic and generic KM framework that could help healthcare organizations to navigate this difficult change process.

关键词： knowledge management Medical services Bioinformatics knowledge transfer Collaboration Biomedical measurements Current measurement knowledge engineering Investments Information technology

FCA2VEC: Embedding techniques for formal concept analysis

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arXiv 2019年

作者： Dürrschnabel, Dominik Hanika, Tom Stubbemann, Maximilian Knowledge and Data Engineering Group University of Kassel Kassel Interdisciplinary Research Center for Information System Design University of Kassel Kassel L3S Research Center Leibniz University Hannover Hannover

Embedding large and high dimensional data into low dimensional vector spaces is a necessary task to computationally cope with contemporary data sets. Superseding 'latent semantic analysis' recent approaches like 'word2vec' or 'node2vec' are well established tools in this realm. In the present paper we add to this line of research by introducing 'fca2vec', a family of embedding techniques for formal concept analysis (FCA). Our investigation contributes to two distinct lines of research. First, we enable the application of FCA notions to large data sets. In particular, we demonstrate how the cover relation of a concept lattice can be retrieved from a computational feasible embedding. Secondly, we show an enhancement for the classical node2vec approach in low dimension. For both directions the overall constraint of FCA of explainable results is preserved. We evaluate our novel procedures by computing fca2vec on different data sets like, wiki44 (a dense part of the Wikidata knowledge graph), the Mushroom data set and a publication network derived from the FCA *** Codes 68T30, 03G10, 06A06 Copyright © 2019, The Authors. All rights reserved.

关键词： Vector spaces

Machine learning approach for segmenting glands in colon histology images using local intensity and texture features

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arXiv 2019年

作者： Khatun, Rupali Chatterjee, Soumick Dept of Computer Applications Amity University Kolkata India Biomedical Magnetic Resonance Faculty of Natural Science Data & Knowledge Engineering Group Faculty of Computer Science Otto von Guericke University Magdeburg Germany

— Colon Cancer is one of the most common types of cancer. The treatment is planned to depend on the grade or stage of cancer. One of the preconditions for grading of colon cancer is to segment the glandular structures of tissues. Manual segmentation method is very time-consuming, and it leads to life risk for the patients. The principal objective of this project is to assist the pathologist to accurate detection of colon cancer. In this paper, the authors have proposed an algorithm for an automatic segmentation of glands in colon histology using local intensity and texture features. Here the dataset images are cropped into patches with different window sizes and taken the intensity of those patches, and also calculated texture-based features. Random forest classifier has been used to classify this patch into different labels. A multilevel random forest technique in a hierarchical way is proposed. This solution is fast, accurate and it is very much applicable in a clinical setup. Copyright © 2019, The Authors. All rights reserved.

关键词： Histology

Realizability of Rectangular Euler Diagrams

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arXiv 2024年

作者： Dürrschnabel, Dominik Priss, Uta Knowledge & Data Engineering Group University of Kassel Kassel Germany Interdisciplinary Research Center for Information System Design Kassel Germany Faculty of Computer Science Ostfalia University of Applied Sciences Wolfenbüttel Germany

Euler diagrams are a tool for the graphical representation of set relations. Due to their simple way of visualizing elements in the sets by geometric containment, they are easily readable by an inexperienced reader. Euler diagrams where the sets are visualized as aligned rectangles are of special interest. In this work, we link the existence of such rectangular Euler diagrams to the order dimension of an associated order relation. For this, we consider Euler diagrams in one and two dimensions. In the one-dimensional case, this correspondence provides us with a polynomial-time algorithm to compute the Euler diagrams, while the two-dimensional case is linked to an NP-complete problem which we approach with an exponential-time *** Codes 06A07, 68R05 Copyright © 2024, The Authors. All rights reserved.

关键词： Formal concept analysis

Towards a practical healthcare information security model for healthcare institutions

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Towards a practical healthcare information security model fo...

IEEE EMBS International Conference on Information Technology Applications in Biomedicine (ITAB)

作者： A. Dwivedi R.K. Bali M.A. Belsis R.N.G. Naguib P. Every N.S. Nassar BIOCORE School of Mathematical and Information Sciences Coventry University UK Data and Knowledge Engineering Research Group (DKERG) School of Mathematical and Information Sciences Coventry University UK Biotech Associates Limited Coventry UK

In recent years, a number of countries have introduced plans for national electronic patient record (EPR) systems. This paper argues that, in the near future, both patients and healthcare stakeholders will be able to access medical records from WWW-based EPR systems. We contend that the primary impediment to the successful implementation and widespread uptake of the EPR concept is the fact that current healthcare information security (HIS) applications are not sufficiently robust. This paper identifies two main Information Security technologies: 1) Public key infrastructure (PKI) and 2) Biometrics that hold a lot of promise in a healthcare context. The key contribution of this paper is to propose a novel multi-layered HIS framework based on a combination of PKI, Smartcard and Biometrics technologies. We argue that this new HIS framework could assist healthcare institutions to provide a truly secure infrastructure for the electronic transmission of clinical data in the future. This paper also makes a case for the creation of a new nodal HIS body because existing information security bodies like the Forum of Incident Response and Security Teams are for general-purpose organizations and not specifically suited for the healthcare sector.

关键词： Medical services Information security Paramagnetic resonance Biometrics Public key Electronic medical prescriptions Mathematical model knowledge engineering Impedance Robustness

Intrinsic dimension and its application to association rules

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arXiv 2018年

作者： Hanika, Tom Schneider, Friedrich Martin Stumme, Gerd Knowledge & Data Engineering Group University of Kassel Germany Institute of Algebra TU Dresden Dresden01062 Germany Departamento de Matemática UFSC Trindade Florianópolis SC88.040-900 Brazil

The curse of dimensionality in the realm of association rules is twofold. Firstly, we have the well known exponential increase in computational complexity with increasing item set size. Secondly, there is a related curse concerned with the distribution of (spare) data itself in high dimension. The former problem is often coped with by projection, i.e., feature selection, whereas the best known strategy for the latter is avoidance. This work summarizes the first attempt to provide a computationally feasible method for measuring the extent of dimension curse present in a data set with respect to a particular class machine of learning procedures. This recent development enables the application of various other methods from geometric analysis to be investigated and applied in machine learning procedures in the presence of high dimension.68T01 68T05 Copyright © 2018, The Authors. All rights reserved.

关键词： Association rules