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检索条件"任意字段=Knowledge-Based Software Engineering Conference"

共 17431 条记录，以下是201-210 订阅

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On the Use of Ontologies for Defining, Generating and Exploring the Resulting Simulations of Application Level Protocols 16

On the Use of Ontologies for Defining, Generating and Explor...

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16th International conference on knowledge engineering and Ontology Development, KEOD 2024 as part of 16th International Joint conference on knowledge Discovery, knowledge engineering and knowledge Management, IC3K 2024

作者： Kokar, Mieczyslaw M. Moskal, Jakub J. Department of Electrical and Computer Engineering Northeastern University 360 Huntington Avenue Boston United States VIStology Inc. MashpeeMA United States

ISBN: (纸本)9789897587160

This paper presents a simulator generator designed to aid in the development of domain-specific protocols that enable semantic communication, where messages include annotations specifying the meaning of individual fields. Furthermore, the field types are dynamic, meaning they are incorporated into messages based on the domain’s underlying ontology. To experiment with such domain-specific semantic protocols, designers require data for protocol evaluation. Simulation is a common solution to this need. Simulations are produced by simulators—software systems that take inputs and generate results. For typical applications, generic simulators are often available. This paper introduces a system, named dg, that generates simulators for semantic communication protocol designers, based on specifications (inputs and constraints) provided in an ontology. Additionally, we demonstrate how the same ontology can be used to explore simulation results. Finally, since our approach involves policies that account for information uncertainty in both simulator implementation and result querying, we propose initiating an effort to develop an uncertainty-related extension to the SPARQL query language. © 2024 by Paper published under CC license (CC BY-NC-ND 4.0).

关键词： Structured Query Language

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Mid-ship Section Optimization using Domain knowledge-based Multilevel Grouping and Cooperative Bayesian Optimization 34th

Mid-ship Section Optimization using Domain Knowledge-based M...

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34th International Ocean and Polar engineering conference, ISOPE 2024

作者： Jiang, Puyu Liu, Jun Cheng, Yuansheng School of Naval Architecture and Ocean Engineering Huazhong University of Science and Technology Hubei Wuhan China

ISBN: (纸本)9781880653784

This work combines structural mechanical prior knowledge with cooperative Bayesian optimization framework and proposes a domain knowledge-based multilevel grouping approach for mid-ship section optimization. Cooperative Bayesian optimization framework decomposes the original high-dimensional problem into a series of lowdimensional subproblems, which are then solved separately using Bayesian optimization. To further improve the efficiency, this work utilizes domain knowledge to group the design variables multiple times during the optimization process. The first level groups the panel thickness and stiffeners sizes separately. The second level groups the panel thickness and the attached stiffeners sizes as a subproblem. The third level groups the panel thickness that share common stiffeners sizes, along with the stiffeners sizes as a subproblem. The optimization order of subproblems (i.e., resource allocation strategy) is also determined based on domain knowledge in this work. In the first level, panel thickness, size of bulb flats, and size of T-sections are optimized sequentially. In the remaining levels, closer variables are prioritized for optimization based on their distances from the neutral axis. The effectiveness of the proposed method is validated through a case study of an oil tanker mid-ship section with 96 design variables and 1191 constraints using the Mars2000 software based on the Common Structural Rules (CSR). Computational results demonstrate that the optimized solution obtained by the proposed method achieved a reduction of 5.94% in mid-ship section area compared with the initial design scheme. The result obtained by the proposed method with less burden is better than that of the state-of-the-art method and classical metaheuristic algorithms. The domain knowledge-based multilevel grouping strategy effectively enhances the performance of cooperative Bayesian optimization framework. © 2024 by the International Society of Offshore and Polar Engineers (I

关键词： Arctic engineering

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Evaluating Transfer Learning for Simplifying GitHub READMEs 2023

Evaluating Transfer Learning for Simplifying GitHub READMEs

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31st ACM Joint Meeting of the European software engineering conference / Symposium on the Foundations-of-software-engineering (ESEC/FSE)

作者： Gao, Haoyu Treude, Christoph Zahedi, Mansooreh Univ Melbourne Melbourne Vic Australia

ISBN: (纸本)9798400703270

software documentation captures detailed knowledge about a software product, e.g., code, technologies, and design. It plays an important role in the coordination of development teams and in conveying ideas to various stakeholders. However, software documentation can be hard to comprehend if it is written with jargon and complicated sentence structure. In this study, we explored the potential of text simplification techniques in the domain of software engineering to automatically simplify GitHub README files. We collected software-related pairs of GitHub README files consisting of 14,588 entries, aligned difficult sentences with their simplified counterparts, and trained a Transformer-based model to automatically simplify difficult versions. To mitigate the sparse and noisy nature of the software-related simplification dataset, we applied general text simplification knowledge to this field. Since many general-domain difficult-to-simple Wikipedia document pairs are already publicly available, we explored the potential of transfer learning by first training the model on the Wikipedia data and then fine-tuning it on the README data. Using automated BLEU scores and human evaluation, we compared the performance of different transfer learning schemes and the baseline models without transfer learning. The transfer learning model using the best checkpoint trained on a general topic corpus achieved the best performance of 34.68 BLEU score and statistically significantly higher human annotation scores compared to the rest of the schemes and baselines. We conclude that using transfer learning is a promising direction to circumvent the lack of data and drift style problem in software README files simplification and achieved a better trade-off between simplification and preservation of meaning.

关键词： software Documentation GitHub Text Simplification Transfer Learning

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Integrating DGBL and Collaborative Learning in Enterprise Resource Planning Courses for Students with engineering Background 26th

Integrating DGBL and Collaborative Learning in Enterprise Re...

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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： May, Ming-Der Lunghwa Univ Sci & Technol Dept Ind Management Taoyuan Taiwan

ISBN: (纸本)9783031519789;9783031519796

Although the current ERP (Enterprise Resource Planning) course has the latest information system software as in the industry that can be operated in class, and with the refinement of PBL and teaching methods, students can learn from the perspective of system implementation, rather than the traditional system operation level. However, for most students, they are still more inclined to work data input, and cannot connect to process-oriented knowledge, or even processes analysis, causing students to fall into repetitive and monotonous system operations. Therefore, this study intends to apply the digital online game competition in the ERP courses of the technical University students. To evaluate the "game-based teaching plan and course design strategy", a statistical comparative analysis is carried out on the impact of the ERP course plan. It is hoped that through such an instructional design integrating PBL and game-based learning, it can encourage students' spontaneous and interesting learning motivation and improve the effect of learning participation.

关键词： Digital game-based-learning Online business game Enterprise resource planning

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Joint Extraction of Interaction Features and Attention Mechanism Fused with Entity-Relations 36

Joint Extraction of Interaction Features and Attention Mecha...

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

作者： Su, Lisha Yan, Rong College of Computer Science Inner Mongolia University Inner Mongolia Key Laboratory of Multilingual Artificial Intelligence Technology National & Local Joint Engineering Research Center of Intelligent Information Processing Technology for Mongolian Hohhot010021 China

ISBN: (纸本)1891706594

Joint extraction of entities and relations is an essential task in information extraction. Recently, tagging-based models have gained attention but with poor performance on overlapping triplets, which confronted the issues like cascading errors, information redundancy, and sensitivity to subject extraction. To solve the issue of overlapping triplets, we propose a model combined Gated Attention Unit (GAU) and Multi-head Attention Mechanism (MHA) in this paper. This model distinguishes features for entities and relations, and performs entity recognition for each head entity, different head entities are matched to the same or different tail entities. Then specific tail entity tagging is applied to determine all possible relations and corresponding tails. At the same time, in order to better solve the long-distance dependence and complex multiple relations between entities, GAU and MHA are used to enhance the semantic representation, effectively identify entities and relations, and enhance the learning ability and generalization ability of the model. Experiment results on the public datasets DuIE2.0 and CMeIE show that our model performs better than baselines. © 2024 knowledge Systems Institute Graduate School. All rights reserved.

关键词： Semantics

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GAT-Team: A Team Recommendation Model for Open-Source software Projects 35

GAT-Team: A Team Recommendation Model for Open-Source Softwa...

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35th International conference on software engineering and knowledge engineering, SEKE 2023

作者： Qi, Qing Cao, Jian Wang, Duo Department of Computer Science and Engineering Shanghai Jiao Tong University Shanghai China

The active participation of contributors is key to the success of any open source software (OSS) projects. In the open source community, it can be found that some developers have participated together in multiple projects and also built social connections so that they form an independent team. Independent teams can be high-quality developer candidates for OSS projects. By modeling the developers and independent teams, we design approaches to recommend independent teams to OSS projects. We used the interaction data between developers to build the developers’ social connection network, on which independent teams can be discovered by utilizing the community discovery algorithm. based on the graph attention network, we designed a team recommendation model GAT-team. The performance of the GAT-team is evaluated on a real-world dataset. GAT-team achieves much better results compared with the other algorithms in the experiments. We provide the data and the code at https://***/10.5281/zenodo.4646651. © 2023 knowledge Systems Institute Graduate School. All rights reserved.

关键词： Recommender systems

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New technologies in the educational process on the example of FlexSim® software - the digital twin solution 28th

New technologies in the educational process on the example o...

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28th International conference on knowledge based and Intelligent information and engineering Systems, KES 2024

作者： Ubowska, Agnieszka Królikowski, Tomasz Faculty of Maritime Technology and Transport West Pomeranian University of Technology in Szczecin Szczecin71-065 Poland Faculty of Mechanical Engineering Koszalin University of Technology Koszalin75- 453 Poland

Access to new technologies in the educational process and developing digital competences enabling critical and responsible use of digital technologies, including future professional work is a challenge for universities around the world. The aim of the article is to indicate the possibilities of using FlexSim® software in the educational process at technical universities. The ability of engineering staff to use simulation methods that reproduce real systems can significantly improve the logistics of processes implemented by enterprises, and thus increase the competitiveness of future graduates on the labor market. The article presents the possibilities of solving selected engineering problems using FlexSim® software and the results of a survey on the usefulness of the software conducted among students. © 2024 The Authors.

关键词： Educational technology

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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...

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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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Channeling the Voice of the Crowd: Applying Structured Queries in User Feedback Collection 30th

Channeling the Voice of the Crowd: Applying Structured Queri...

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30th International Working conference on Requirements engineering - Foundation for software Quality (REFSQ)

作者： Radeck, Leon Paech, Barbara Heidelberg Univ Inst Comp Sci D-69120 Heidelberg Germany

ISBN: (纸本)9783031573262;9783031573279

[Context/Motivation] Crowd-based Requirements engineering (CrowdRE) promises to overcome limitations of traditional requirements engineering by actively involving a larger number of users. A common theme in CrowdRE research is the development and deployment of online platforms where users can autonomously provide their feedback about software. [Problems] Current platforms only provide minimal guidance regarding the topics mentioned in the feedback. Therefore, it is difficult tomap the feedback to existing requirements and identify gaps. [Principal ideas] To address the problems, we present a systematic process for collecting feedback through a variety of structured questions and an online platform which supports the process. We evaluate the process and the platform in the large-scale interdisciplinary research project SMART-AGE. [Contribution] To our best knowledge, this is the first platform that gathers feedback from a large number of users simultaneously through structured queries. Our contributions include a tailored list of questions for feedback collection, an analysis of how the question characteristics influence the answers and an evaluation of the user acceptance. Our findings indicate that both the quality and quantity of feedback are high, with variations based on the characteristics of the questions. Additionally, our platform is well accepted by its users.

关键词： requirements engineering crowd user feedback collection

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Where is it? Tracing the Vulnerability-Relevant Files from Vulnerability Reports 24

Where is it? Tracing the Vulnerability-Relevant Files from V...

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44th ACM/IEEE International conference on software engineering, ICSE 2024

作者： Sun, Jiamou Chen, Jieshan Xing, Zhenchang Lu, Qinghua Xu, Xiwei Zhu, Liming Csiro SydneyNSW Australia Csiro & Australian National University CanberraACT Australia

ISBN: (纸本)9798400702174

With the widely usage of open-source software, supply-chain-based vulnerability attacks, including SolarWind and Log4Shell, have posed significant risks to software security. Currently, people rely on vulnerability advisory databases or commercial software bill of materials (SBOM) to defend against potential risks. Unfortunately, these datasets do not provide finer-grained file-level vulnerability information, compromising their effectiveness. Previous works have not adequately addressed this issue, and mainstream vulnerability detection methods have their drawbacks that hinder resolving this gap. Driven by the real needs, we propose a framework that can trace the vulnerability-relevant file for each disclosed vulnera-bility. Our approach uses NVD descriptions with metadata as the inputs, and employs a series of strategies with a LLM model, search engine, heuristic-based text matching method and a deep learning classifier to recommend the most likely vulnerability-relevant file, effectively enhancing the completeness of existing NVD data. Our experiments confirm that the efficiency of the proposed framework, with CodeBERT achieving 0.92 AUC and 0.85 MAP, and our user study proves our approach can help with vulnerability-relevant file detection effectively. To the best of our knowledge, our work is the first one focusing on tracing vulnerability-relevant files, laying the groundwork of building finer-grained vulnerability-aware software bill of materials. © 2024 ACM.

关键词： Open source software

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