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检索条件"任意字段=19th International Conference on Software Engineering and Knowledge Engineering"

共 37404 条记录，以下是331-340 订阅

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software Product Management in Large-Scale Agile 25th

Software Product Management in Large-Scale Agile

引用

25th international conference on Agile software Development (XP)

作者： Moe, Nils Brede Berntzen, Marthe Barbala, Astri Stray, Viktoria SINTEF Strindveien 4 N-7465 Trondheim Norway Univ Oslo Gaustadalleen 23B N-0373 Oslo Norway Knowit Solut AS Univ Gata 1 N-0164 Oslo Norway

ISBN: (纸本)9783031611537;9783031611544

Large-scale agile software development is increasingly being organized with product management. Although product management is familiar to software engineering, we need research-based knowledge about organizing product management in an agile development context. this study focuses on product management challenges and configurations in a Nordic fintech organization with 10,000 employees. We conducted 19 interviews with participants involved in core product management activities. the study identifies ten key factors that hinder product management performance in a large-scale agile product company. Further, we present six product management configurations used in the fintech organization. the most suitable setup depends on the product lifecycle stage, product size, and development team setup. Our summary of the product management configurations and challenges can guide software product managers working in large-scale agile companies.

关键词： Product Management Team Product Manager Product Owner Agile software Development Coordination

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Fine-grained Image Classification Based on knowledge Distillation 19

Fine-grained Image Classification Based on Knowledge Distill...

引用

19th international conference on Natural Computation, Fuzzy Systems and knowledge Discovery, ICNC-FSKD 2023

作者： Liu, Ying Feng, Hao Zhang, Weidong Fang, Jie Xiao, Peng Zhang, Dengsheng Xi'an University of Posts and Telecommunications Center for Image and Information Processing School of Communications and Information Engineering Shaanxi International Joint-Research Center for Wireless Communication and Information Processing Xi'an China Xi'an University of Posts and Telecommunications Center for Image and Information Processing School of Communications and Information Engineering Xi'an China Institute of Innovation Science & Sustainability Federation University Australia Gippsland Australia

ISBN: (纸本)9798350304398

Despite the outstanding performance of deep learning-based fine-grained image classification methods, the commonly used models still suffer from high cost of computation and memory therefore, this paper proposes a mobile-based CNN network that focuses on discriminative features of fine-grained images by embedding a hybrid-domain attention module to achieve higher accuracy in recognition. Specifically, under the premise of reducing network parameters, this paper presents a classification method that combines transfer learning and knowledge distillation to enhance the model's generalization performance and resistance to overfitting. Different knowledge transfer strategies are validated through the experiments in the knowledge distillation process. Mobile models such as SqueezeNet, MobileNetV2, and CBAM MobileNetV2 all demonstrate enhanced performance the knowledge distillation optimization. the proposed method in this paper can be used to develop a lightweight mobile-based CNN model with comparable performance to complex models making it more advantageous in real-life scenarios with limited storage resources and low hardware computation levels. Additionally, the model compression process utilizes only the intermediate features of the original dataset, meeting the confidentiality requirements of the original data in the field of public security. © 2023 IEEE.

关键词： Image classification

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An Interactive Visual Instrument to Address the Scoping of Bespoke Information Systems

An Interactive Visual Instrument to Address the Scoping of B...

引用

conference on Human Interface and the Management of Information thematic Area (HIMI) Held as Part of the 26th international conference on Human-Computer Interaction (HCII)

作者： Pereira-Vale, Anelis Vera, Tomas Perovich, Daniel Ochoa, Sergio F. Benitti, Fabiane Univ Chile Dept Comp Sci Santiago Chile Zenta Grp Santiago Chile Univ Fed Santa Catarina Dept Informat & Stat Florianopolis SC Brazil

ISBN: (纸本)9783031601064;9783031601071

the literature in requirements engineering recognizes the product scoping activity as an important source of risks and fails in bespoke software projects. In order to help address this activity, we designed and implemented an interactive visual instrument that allows providers and customers to jointly define the scope of bespoke software products, particularly, information systems. the instrument was formally evaluated through a qualitative study that involved three projects in Chile and three in Brazil. Real customers and providers took part in these experiences. the evaluation results were highly encouraging, showing the instrument is a serious candidate to help deal with the product scoping challenges. Customers, software providers and also software engineering researchers can also take advantage of it, by reusing and adjusting the instrument to their own reality.

关键词： software product scoping interactive visual instrument visual knowledge shared space bespoke information systems empirical evaluation

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software Defect Prediction via Code Grayscale Pixel Visualization with Fusion Attention 36

Software Defect Prediction via Code Grayscale Pixel Visualiz...

引用

36th international conference on software engineering and knowledge engineering, SEKE 2024

作者： Qiu, Shaojian Wang, Shaosheng Rong, Wei Liao, Lili Lin, Yishen College of Software Engineering South China Agricultural University China School of Computer Science and Engineering South China University of Technology China Guangdong Tobacco Meizhou Limited Company China

ISBN: (纸本)1891706594

software defect prediction helps quality assurance teams find defects in software, thereby enhancing the reliability of the systems. In existing code-visualization-based defect prediction methods, challenges arise from mixing code information and the potential omission of critical defect features. To enhance the completeness of code features, this paper proposes a defect prediction model based on code grayscale pixel visualization with a fusion attention mechanism (Gpv2DP). Gpv2DP converts code into grayscale images and reshapes the images to a standard size, effectively alleviating the information loss problem caused by element mixing and image cropping. Furthermore, it constructs a code feature extracting network that simultaneously integrates the channel, spatial and 3D attention. We conduct empirical experiments on ten open-source Java projects from the PROMISE repository. the results show that the F-measure and AUC metrics of Gpv2DP outperform related defect prediction methods. © 2024 knowledge Systems Institute Graduate School. All rights reserved.

关键词： software reliability

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Future Skills in software engineering and Health Care - Similar but Different 26th

Future Skills in Software Engineering and Health Care - Simi...

引用

26th international conference on Interactive Collaborative Learning (ICL) - Towards a Hybrid, Flexible and Socially Engaged Higher Education / 52nd IGIP international conference on engineering Pedagogy

作者： Sedelmaier, Yvonne Landes, Dieter SRH Wilhelm Loehe Univ Appl Sci Merkurstr 19 D-90763 Furth Germany Univ Appl Sci Coburg Friedrich Streib Str 2 D-96450 Coburg Germany

ISBN: (纸本)9783031526664;9783031526671

In order to cope with current disruptive technical and societal transformations, e.g. through digitalization or AI, new competences, commonly called future skills, are indispensable for everyday as well as for professional life. Many organizations, large and small, work on defining a set of future skills. this might imply that future skills are generic and identical across all professions. In contrast, it is a consensus in pedagogical research that generic competences are specifically shaped by the professional environment. Clearly, these two positions contradict each other. But what does this contradiction mean for future skills? this research rests on the assumption that these context-sensitive generic competences including future skills are developed differently for each occupational field. In order to be able to offer target- and competence-oriented teaching, target competences must be known in the first place, taking into account the specific professional characteristics, currently and in the future. this paper provides evidence that the initial assumption of context-specific competences is true by collecting and comparing qualitative research data. To do so, qualitative data was collected for different occupations, in particular software engineering and health care. Our research shows that in fact each profession expresses competences specifically, and this applies to technical as well as non-technical competences. the details of relevant competences need to be identified and characterized as a prerequisite for being able to devise and offer competence-oriented learning approaches.

关键词： Future skills health care software engineering

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Bridging the Gap between Academia and Industry in Machine Learning software Defect Prediction: thirteen Considerations 38

Bridging the Gap between Academia and Industry in Machine Le...

引用

38th IEEE/ACM international conference on Automated software engineering (ASE)

作者： Stradowski, Szymon Madeyski, Lech Nokia Mobile Networks Radio Frequency Wroclaw Poland Wroclaw Univ Sci & Technol Dept Appl Informat Wroclaw Poland

ISBN: (纸本)9798350329964

this experience paper describes thirteen considerations for implementing machine learning software defect prediction (ML SDP) in vivo. Specifically, we provide the following report on the ground of the most important observations and lessons learned gathered during a large-scale research effort and introduction of ML SDP to the system-level testing quality assurance process of one of the leading telecommunication vendors in the world - Nokia. We adhere to a holistic and logical progression based on the principles of the business analysis body of knowledge: from identifying the need and setting requirements, through designing and implementing the solution, to profitability analysis, stakeholder management, and handover. Conversely, for many years, industry adoption has not kept up the pace of academic achievements in the field, despite promising potential to improve quality and decrease the cost of software products for many companies worldwide. therefore, discussed considerations hopefully help researchers and practitioners bridge the gaps between academia and industry.

关键词： machine learning software defect prediction Nokia 5G industry introduction experience paper

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3D Scene Graph Prediction on Point Clouds Using knowledge Graphs 19

3D Scene Graph Prediction on Point Clouds Using Knowledge Gr...

引用

19th IEEE international conference on Automation Science and engineering, CASE 2023

作者： Qiu, Yiding Christensen, Henrik I. University of California San Diego Department of Computer Science and Engineering La Jolla 92122 United States

ISBN: (纸本)9798350320695

3D scene graph prediction is a task that aims to concurrently predict object classes and their relationships within a 3D environment. As these environments are primarily designed by and for humans, incorporating commonsense knowledge regarding objects and their relationships can signifi-cantly constrain and enhance the prediction of the scene graph. In this paper, we investigate the application of commonsense knowledge graphs for 3D scene graph prediction on point clouds of indoor scenes. through experiments conducted on a real-world indoor dataset, we demonstrate that integrating external commonsense knowledge via the message passing method leads to a 15.0% improvement in scene graph prediction accuracy with external knowledge and 7.96% with internal knowledge when compared to state-of-the-art algorithms. We also tested in the real world with 10 frames per second for scene graph generation to show the usage of the model in a more realistic robotics setting. © 2023 IEEE.

关键词： Message passing

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Construction and optimization of medical question answering system based on knowledge Graph 23

Construction and optimization of medical question answering ...

引用

23rd IEEE international conference on High Performance Computing and Communications, 7th IEEE international conference on Data Science and Systems, 19th IEEE international conference on Smart City and 7th IEEE international conference on Dependability in Sensor, Cloud and Big Data Systems and Applications, HPCC-DSS-SmartCity-DependSys 2021

作者： Gao, Bing Wang, Hao-Xiong Zou, Qi-Jie Qin, Jing College of Information Engineering Dalian University Dalian China School of Software Engineering Dalian University Dalian China

ISBN: (纸本)9781665494571

Medical question answering system is one of the significant measures to effectively solve common sense queries related to diseases. Aiming at the loose structure, low efficiency, and weak linking of domain knowledge in the current traditional medical model field, this paper constructs a Medical question answering system based on knowledge graph(KG). We achieve the goal of improving classification performance through three aspects, including: (i) creation of a medical KG by building a dictionary and generating entities and relationships, (ii) design of the Bert+TextCnn model combined with the k-nrm text matching algorithm to calculate the question template that is closest to the user's question in the system, and (iii) construct a cypher sentence based on the medical entity and the question template. the experimental results demonstrate that the medical KG question answering system based on intent recognition and k-nrm text matching has a higher accuracy rate than the traditional question answering system, and has a extraordinary question answering ability. © 2021 IEEE.

关键词： Semantics

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A Fact Prediction Model based on Hyper Graph and Neural Network 5

A Fact Prediction Model based on Hyper Graph and Neural Netw...

引用

5th international conference on Big Data and Artificial Intelligence and software engineering, ICBASE 2024

作者： Sun, Hongji Wei, Muchi Li, Jiazhe Xu, Xilei Zhou, Borui Qingdao University of Science and Technology School of Information Science and Technology Qingdao China International College Beijing University of Posts and Telecommunications Beijing China Fujian Medical University School of Medical Imaging Fuzhou China Beijing Jiaotong University School of Electronic Information Engineering Weihai China Qingdao University of Technology College of Information and Control Engineering Qingdao China

ISBN: (纸本)9798331506612

We presents a knowledge graph reasoning model based on neural network, which aims to improve the capability of predicting missing entities in knowledge graphs. Traditional methods often struggle with the prediction of facts as they treat them like unseen entities, leading to poor performance. To address this challenge, we developed a robust representation for facts, leveraging a neural network model enhanced with data augmentation techniques. Our approach is evaluated using two datasets derived from real-world knowledge bases, including FBH and DBHE. these datasets feature a rich structure of associations and higher-level relationships, enhancing the complexity and expressiveness of the knowledge graph. Our experimental results show significant improvements over several state-of-the-art methods in terms of Mean Reciprocal Rank (MRR) and Hits@10, demonstrating the efficacy of our proposed method in predicting both entities and facts accurately. Furthermore, we observed that increasing the number of layers in our neural network model up to a certain point consistently improved performance, indicating the stability and effectiveness of our model. © 2024 IEEE.

关键词： knowledge graph

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Exploring a Research Agenda for Design knowledge Capture in Meetings 16

Exploring a Research Agenda for Design Knowledge Capture in ...

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16th IEEE/ACM international conference on Cooperative and Human Aspects of software engineering (CHASE)

作者： Seero, Liz Burge, Janet Soria, Adriana Meza van der Hoek, Andre Colorado Coll Math & Comp Sci Colorado Springs CO 80903 USA Univ Calif Irvine Informat Irvine CA USA

ISBN: (纸本)9798350337341

Meetings are a frequent part of life for a software developer. software design is often performed, discussed, and reviewed in these meetings. this means that meetings may contain important design information that could be captured for later use. Meeting design tools may be a way to capture design information as a byproduct of discussion that arises in these meetings. In this paper, we identify a list of key meeting support tool features that could support the capture and retrieval of design information and compare these to features currently offered in commercial meeting support tools.

关键词： software design design meetings design rationale tools

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