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15th CCF conference on computer supported cooperative work and social computing, Chinese CSCW 2020

作者： Xie, Yi Wang, Shaoqing Pan, Wei Tang, Huaibin Sun, Yuqing School of Software Shandong University Jinan China School of Computer Science and Technology Shandong University Jinan China School of Microelectronics Shandong University Jinan China Engineering Research Center of Digital Media Technology Shandong University Jinan China

ISBN: (纸本)9789811625398

It is meaningful for researchers to find the interested and high quality new papers. We propose the Joint Text and Influence Embedding recommendation model (JTIE) to consider both the paper quality and the content correlation. We train a paper embedding based on its core elements: contents, authors and publication venues. The quality of a new paper is evaluated based on the author authority and the venue reputation. The citation relationships between papers are considered asymmetric such that they can reflect the user’s consideration on the intrinsic influence of a paper. We learn user interests by one’s historical references or a set of query keywords. Finally, papers are recommended according to the relatedness between user interests and paper embeddings. We perform experiments against three real-world datasets. The results show that our model outperforms baseline methods on both the personalized recommendation and the query keywords based retrieval. © 2021, Springer Nature Singapore Pte Ltd.

关键词： Embeddings

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A New Collaborative Scheduling Mechanism Based on Grading Mapping for Resource Balance in Distributed Object Cloud Storage System 16th

A New Collaborative Scheduling Mechanism Based on Grading Ma...

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16th EAI International conference on Collaborative computing: Networking, Applications, and worksharing, CollaborateCom 2020

作者： Lu, Yu Chen, Ningjiang Pu, Wenjuan Wang, Ruifeng School of Computer and Electronic Information Guangxi University Nanning530004 China Guangxi Key Laboratory of Multimedia Communications and Network Technology Nanning530004 China

ISBN: (纸本)9783030675394

An algorithmic mapping of storage locations brings high storage efficiency to the storage system, but the loss of efficient scheduling makes systems prone to crashing at low usage. This paper uses the Ceph storage system as a research sample to analyze these issues and proposes a grading mapping adaptive storage resource collaborative optimization mechanism. This approach grading both the storage device and the storage content, and introduced random factors and influence factors as two-factors to quantify the grading mapping relationship between the two of them. This relation coordinates the storage systems’ performance and reliability. In addition, a collaborative storage algorithm is proposed to realize balanced storage efficiency and control data migration. The experimental results show that in comparison with the inherent mechanism in the traditional Ceph system, the proposed cooperative storage adaptation mechanism for data balancing has increased the average system usage by 17% and reduces data migration by 50% compared to the traditional research approach. © 2021, ICST Institute for computer Sciences, social Informatics and Telecommunications Engineering.

关键词： Mapping

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Research on Machine Learning Method for Equipment Health Management in Industrial Internet of Things 15th

Research on Machine Learning Method for Equipment Health Man...

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15th CCF conference on computer supported cooperative work and social computing, Chinese CSCW 2020

作者： Tan, Zheng Wen, Yiping School of Computer Science and Engineering Hunan University of Science and Technology Xiangtan China Key Laboratory of Knowledge Processing and Networked Manufacturing Hunan University of Science and Technology Xiangtan China

ISBN: (纸本)9789811625398

Much industrial equipment integrates multiple types of sensors for data collection and real-time connection with the Industrial Internet of Things (IIoT) at now. With the popularity and application of miniaturized and low-cost sensors, to manage the health of equipment in the IIoT, such as evaluating the current health indicator (HI) of the equipment, and predicting its remaining useful life (RUL), the machine learning-based method reflects a broader application prospect due to its good at data mining and analysis. A RUL prediction method of equipment in this paper is proposed. First, a specific data processing method is proposed according to the characteristics of the data, the outputs of the hidden layer of stacked denoising autoencoder (SDAE) as the features of the data set which are extracted to complete the HI construction. Then, the trajectory pointwise difference and similarity method are proposed to generate predicted equipment RUL. This paper uses the C-MAPSS engine data set for experimental verification. The experimental results show that the method proposed in this paper can effectively use the data of multi-dimensional sensor data to get the degradation progress of the equipment, thereby assessing the health of the equipment and more accurately estimating the RUL. © 2021, Springer Nature Singapore Pte Ltd.

关键词： Internet of things

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Creating business model canvases with a collaborative mobile application 17

Creating business model canvases with a collaborative mobile...

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17th European conference on computer supported cooperative work, ECSCW 2019

作者： Kühn, Romina Korzetz, Mandy Kegel, Karl Aßmann, Uwe TU Dresden Software Technology Group Dresden Germany

Business models are important for both start-ups and established companies because they form the basis for a company's success by outlining their key factors. Business models can be created and documented in several ways. We focus on Business Model Canvases (BMC) and present MobiLean, a mobile application for the collaborative creation of BMCs. MobiLean is an easy and interactive smartphone app for groups of varying size in mixed-focus collaboration scenarios. We apply mobile-based interactions for the ease of use and the support of the creativity process. We contribute to the field of CSCW by providing a mobile application for the domain of co-working and aim to demonstrate how MobiLean supports creating, revising, and documenting BMCs. © 2019 by Authors.

关键词： Mobile computing

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Dynamic Vehicle Distribution Path Optimization Based on Collaboration of Cloud, Edge and End Devices 15th

Dynamic Vehicle Distribution Path Optimization Based on Coll...

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15th CCF conference on computer supported cooperative work and social computing, Chinese CSCW 2020

作者： Li, Tiancai Wen, Yiping Tan, Zheng Chen, Hong Cao, Buqing School of Computer Science and Engineering Hunan University of Science and Technology Xiangtan China Key Laboratory of Knowledge Processing and Networked Manufacturing Hunan University of Science and Technology Xiangtan China

ISBN: (纸本)9789811625398

Aiming at the problems of unreasonable distribution routes in the current logistics distribution field, without considering the impact of real-time road conditions, and the inability to reduce the impact on the timeliness of distribution, this paper proposes a dynamic vehicle distribution path optimization method based on the collaboration of cloud, edge and end devices. This method considers the requirements of demand points for the delivery time and considers the changes in road traffic conditions caused by random road traffic incidents. Combining the characteristics of vehicle speed and time penalty cost in the vehicle delivery process establishes a logistics delivery vehicle path optimization model. Solve it and optimize it with the A* algorithm and dynamic schedule. This method collects road condition data in real-time through terminal equipment, evaluates and judges road conditions at the edge, and makes real-time adjustments to the distribution plan made in advance at the cloud data center. Through simulation experiments on application examples, the vehicle path optimization method proposed in this paper that considers real-time road conditions changes and the optimization method that does not consider road conditions are compared and analyzed, verifying the effectiveness of this method. Experimental results show that this method can reduce distribution costs, reduce distribution time, and reduce the impact of changes in road conditions on the distribution results. © 2021, Springer Nature Singapore Pte Ltd.

关键词： Vehicles

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A Light Transfer Model for Chinese Named Entity Recognition for Specialty Domain 15th

A Light Transfer Model for Chinese Named Entity Recognition ...

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15th CCF conference on computer supported cooperative work and social computing, Chinese CSCW 2020

作者： Wu, Jiaqi Liu, Tianyuan Sun, Yuqing Gong, Bin School of Software Shandong University Jinan China Engineering Research Center of Digital Media Technology Shandong University Jinan China School of Computer Science and Technology Shandong University Jinan China

ISBN: (纸本)9789811625398

Named entity recognition (NER) for specialty domain is a challenging task since the labels are specific and there are not sufficient labelled data for training. In this paper, we propose a simple but effective method, named Light Transfer NER model (LTN), to tackle this problem. Different with most traditional methods that fine tune the network or reconstruct its probing layer, we design an additional part over a general NER network for new labels in the specific task. By this way, on the one hand, we can reuse the knowledge learned in the general NER task as much as possible, from the granular elements for combining inputs, to higher level embedding of outputs. On the other hand, the model can be easily adapted to the domain specific NER task without reconstruction. We also adopt the linear combination on each dimension of input feature vectors instead of using vector concatenation, which reduces about half parameters in the forward levels of network and makes the transfer light. We compare our model with other state-of-the-art NER models on real datasets against different quantity of labelled data. The experimental results show that our model is consistently superior than baseline methods on both effectiveness and efficiency, especially in case of low-resource data for specialty domain. © 2021, Springer Nature Singapore Pte Ltd.

关键词： Light transmission

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Attention-Aware Actor for cooperative Multi-agent Reinforcement Learning 17th

Attention-Aware Actor for Cooperative Multi-agent Reinforce...

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17th EAI International conference on Collaborative computing: Networking, Applications, and worksharing, CollaborateCom 2021

作者： Zhao, Chenran Shi, Dianxi Zhang, Yaowen Su, Yaqianwen Zhang, Yongjun Yang, Shaowu National University of Defense Technology Changsha410073 China Beijing100166 China Tianjin300457 China Environment Information Support 32282 Research Institute Jinan250000 China

ISBN: (纸本)9783030926373

In multi-agent environments, cooperation is crucially important, and the key is to understand the mutual interplay between agents. However, multi-agent environments are highly dynamic, where the complex relationships between agents cause great difficulty for policy learning, and it’s costly to take all coagents into consideration. Besides, agents may not be allowed to share their information with other agents due to communication restrictions or privacy issues, making it more difficult to understand each other. To tackle these difficulties, we propose Attention-Aware Actor (Tri-A), where the graph-based attention mechanism adapts to the dynamics of the mutual interplay of the multi-agent environment. The graph kernels capture the relations between agents, including cooperation and confrontation, within local observation without information exchange between agents or centralized processing, promoting better decision-making of each coagent in a decentralized way. The refined observations produced by attention-aware actors are exploited to learn to focus more on surrounding agents, which makes Tri-A act as a plug for existing multi-agent reinforcement learning (MARL) methods to improve the learning performance. Empirically, we show that our method substantially achieves significant improvement in a variety of algorithms. © 2021, ICST Institute for computer Sciences, social Informatics and Telecommunications Engineering.

关键词： Graphic methods

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Profiling Hate Speech Spreaders on Twitter: Transformers and mixed pooling

Profiling Hate Speech Spreaders on Twitter: Transformers and...

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2021 working Notes of CLEF - conference and Labs of the Evaluation Forum, CLEF-WN 2021

作者： Huertas-García, Álvaro Huertas-Tato, Javier Martín, Alejandro Camacho, David Department of Computer System Engineering Universidad Politécnica de Madrid Calle de Alan Turing Madrid28031 Spain Department of Computer Sciences Universidad Rey Juan Carlos Calle Tulipán Madrid28933 Spain

The growth of Online social Networks (OSNs) has originated an increasing presence of online hate-spreaders. This fact undermines the integrity of online conversations by sharing inflammatory claims that influence public opinion while sow conflict on social or political issues. In this work, we propose a system for Authors Profiling Hate Speech Spreaders in the Twitter Spanish and English tasks at PAN@CLEF 2021. We present a hybrid system that uses Transformer-based models as feature extractors at the tweet level in combination with mixed pooling techniques. This approach allows computing the author's representative embeddings, which later fed an ML classifier. We explore the incorporation of features from Transformer-based models, Sentiment Analysis, and Hate lexicons to boost the feature extraction process. The results show that through this approach, it is possible to achieve 67% and 78% accuracy in the English and Spanish test datasets. © 2021 Copyright for this paper by its authors. Use permitted under Creative Commons License Attribution 4.0 International (CC BY 4.0).

关键词： Spreaders

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Editor's welcome

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proceedings of the acm on Human-computer Interaction 2019年第GROUP期3卷 1–2页

作者： Erickson, Ingrid Vivacqua, Adriana S. Christensen, Lars Rune Holten Møller, Naja L. Baumer, Eric Wohn, Yvette Barkhuus, Louise Robert, Lionel P. Syracuse University United States Federal University of Rio de Janeiro Brazil IT University of Copenhagen Denmark University of Copenhagen Denmark Lehigh University United States NJIT United States University of Michigan United States

It is our pleasure to welcome you to the first PacmHCI GROUP issue. For over 25 years, the GROUP research community has supported the development of robust scholarship at the intersection of computer supported cooperative work, Human computer Interaction, computer supported Collaborative Learning and Socio-Technical Studies. This volume is the latest product of our efforts to validate and integrate the strong work happening within this broadly-conceived *** hope that the range of papers presented here reflects our intent to be international, interdisciplinary, and inclusive, both in our organization of the review process as well as within the set of accepted papers. This first Pacm journal volume in the GROUP series features studies of collaboration in multiple settings, including social networks, editing systems, and mixed reality. It also showcases sociotechnical studies in domains ranging from outdoor activities to scientific projects.

关键词： collaborative computing computer suported cooperative work social computing

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Evaluating ask izzy: A mobile web app for people experiencing homelessness 17

Evaluating ask izzy: A mobile web app for people experiencin...

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17th European conference on computer supported cooperative work, ECSCW 2019

作者： Burrows, Rachel Mendoza, Antonette Sterling, Leon Miller, Tim Pedell, Sonja School of Computing and Information Systems University of Melbourne Australia Centre for Design Innovation Swinburne University of Technology Australia PsyLab Cambridge Science Park United Kingdom

This paper contributes to an ongoing discussion in the research community regarding the role of new technology in the lives of those experiencing homelessness. Ask Izzy is a mobile web app designed to help people who are homeless or at risk of becoming homeless find the services they need. Since deployment in 2016, it is now attracting over 10,000 users each month. We explore the perceptions towards the design and use of Ask Izzy with a specific focus on emotional concerns. We interviewed 30 participants who were either homeless, ex-homeless, service providers or software developers of the web application. Seven themes emerged from the analysis that appeared to act as barriers or enablers to the uptake of the technology. We discuss how these themes are associated with aspects of technology design or an associated experience with a service provider. We also contrast the views of those who are homeless with service providers. We believe these themes will provoke discussion and be useful for others who are designing for those who are homeless. © 2019 held by Authors.

关键词： Behavioral research

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