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

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CRCC: Collaborative Relation Context Consistency on the knowledge Graph for Recommender Systems 35

CRCC: Collaborative Relation Context Consistency on the Know...

引用

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

作者： Wang, Li-E Zeng, Huachang Li, Shenghan Li, Xianxian Zhuo, Shengda Xie, Jiahua Qu, Bin Sun, Zhigang Liu, Tianran School of Computer Science and Engineering Guangxi Normal University Guilin China Guangxi Key Lab of Multi-source Information Mining Security Guangxi Normal University Guilin China Key Lab of Education Blockchain and Intelligent Technology Ministry of Education Guangxi Normal University Guilin China College of Cyber Security of Jinan University Jinan University Guangzhou China School of Information Science and Engineering Yunnan University Kunming China

knowledge graph (KG) as auxiliary information can solve the cold-start and data sparsity problems of recommender systems. However, most existing KG-based recommendation methods focus on how to effectively encode items with that users have interacted into entities and propagate them explicitly, but neglect the relation-level and context-level modeling of collaborative signals. Therefore, it is inevitable to incorporate some unrelated entities while utilizing a propagation strategy, which may weaken part of the recommendation performance. To address this problem, we propose a novel method named Collaborative Relation Context Consistency (CRCC). Compared with other KG-based methods, we model the relation-level and context-level of collaborative signals in a fine-grained manner. Specifically, we segment the user’s collaborative knowledge graph to learn related entity information separately to enrich the embedding of users. Moreover, CRCC links the consistency score between the items that users and neighbors have interacted with as the fusion basis, and then we consider the inherent popularity of items while incorporating consistent entities to enhance the embedding representation of items. Extensive experiments on three real-world datasets show that CRCC outperforms several compelling baselines in both CTR prediction and top-K recommendation. © 2023 knowledge Systems Institute Graduate School. All rights reserved.

关键词： Recommender systems

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Manual and Automated Web-based Testing of the NPTEL Portal

Manual and Automated Web-based Testing of the NPTEL Portal

引用

2023 International conference on Artificial Intelligence and knowledge Discovery in Concurrent engineering, ICECONF 2023

作者： Shree, N. Durga Mathew, D.A. Steve Gitanjali, J. School of Information Technology and Engineering Vellore Institute of Technology Vellore India

ISBN: (纸本)9798350334357

The NPTEL (National Programme on Technology Enhanced Learning) program is an initiative to provide accessibility to the resources of well-structured courses that are developed in the reputed institutions of the country. In this study, we attempt to identify the correctness, completeness, and quality of the developed NPTEL web portal. In the many forms and page redirects, we attempt to test the validation of input fields and performance using the automated software testing tool, Selenium. By incorporating the black-box testing strategy and its conditions, the NPTEL portal and its subsidiary portal, the GATE portal, were tested. The goal of the study is to analyse the presence of vulnerabilities in the NPTEL Portal and assess it for robustness and adaptability. © 2023 IEEE.

关键词： Portals

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Enhancing Named Entity Recognition in Safety Hazard Analysis through GBD and LLMs 7

Enhancing Named Entity Recognition in Safety Hazard Analysis...

引用

7th International conference on Information and Computer Technologies, ICICT 2024

作者： Dong, Haoling Wu, Bin Beijing University Of Post And Telecommunications School Of Computer Science National Pilot Software Engineering School Beijing China

ISBN: (纸本)9798350385625

With the continuous enhancement of informatization in production safety, the need to strengthen the analysis capability of big data in production safety is increasingly growing. This is crucial for preventing major accidents and ensuring production safety. However, the main challenge currently faced is that information about safety hazards often appears in unstructured text formats, lacking a unified standard and normative system. This makes it difficult to standardize knowledge extraction from hazard information. Additionally, traditional named entity recognition methods arc inadequate in understanding sentence structures, lexical components, and the dependency relationships between words, especially in processing texts in specific complex domains, where their entity recognition effects arc still insufficient. Given this, the research focus of this paper includes: deeply exploring the concept and connotation of big data in hazard information, clarifying the classification system of hazard information;designing a standard hazard information annotation template specifically for the field of production safety;designing a named entity recognition method based on GBD;designing and implementing a named entity recognition method based on LLMs;and based on the recognition results, constructing a knowledge graph of the relevant field to promote its effective utilization in practical applications. © 2024 IEEE.

关键词： Hazards

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Research on Genetic Quantum Particle Swarm Optimization Fusion Algorithm in Virtual Machine Scheduling 24

Research on Genetic Quantum Particle Swarm Optimization Fusi...

引用

2nd International conference on Educational knowledge and Informatization, EKI 2024

作者： Gan, Weimin Li, Jianhui Department of Network Technology Software Engineering Institute of Guangzhou China

ISBN: (纸本)9798400710230

With the rapid development of cloud computing technology, virtual machine scheduling has become an important means to ensure the performance, efficiency, and reliability of cloud services. In response to the shortcomings of traditional virtual machine scheduling algorithms in optimization efficiency and global search ability, this paper proposes a virtual machine scheduling method based on genetic quantum particle swarm fusion algorithm. This algorithm improves the convergence speed and solution quality of the algorithm by introducing mechanisms such as quantum particle swarm optimization and genetic algorithm. The experimental results show that the algorithm achieves precise and efficient virtual machine scheduling, optimizing resource mapping from virtual machines to physical hosts. © 2024 Copyright held by the owner/author(s).

关键词： Scheduling algorithms

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To Communicate or not to Communicate: That is the Problem 16

To Communicate or not to Communicate: That is the Problem

引用

16th International conference on ENTERprise Information Systems, CENTERIS 2024 - 12th International conference on Project MANagement, ProjMAN 2024 - 14th International conference on Health and Social Care Information Systems and Technologies, HCist 2024

作者： Alkhatib, Ghazi P.O. Box 330127 Zarqa13133 Jordan

The main objective of this paper is to demonstrate the complexity and perils of communication patterns between all parties involved throughout the software development life phases. Such communication takes place from the inception of information systems until re-engineering or retirement. For this aim, the paper develops a communication-based framework of information systems (CFIS) identifying major stakeholders involved and languages/models/methodologies deployed during system development and used as a means to document requirements and as a communication method to convey such requirements to end users. The salient feature of such a framework is that it takes several consecutive communication channels with varying communication media and stakeholders. Two types of communication views are delineated. The internal view has two major stakeholders, namely end users and IT professionals. The external view, on the other hand, represents the communication between the internal parties and the external parties, such as the government and vendors. Borrowing from telecommunication theory, two sources of errors are identified: distortion and noise. Distortion, which will refer to it as the error, applies to the internal view, and noise is attributed to the external view. The paper identifies several sources of error and noise and corresponding techniques to tackle them. The author hopes that this paper will assist in improving software quality, reducing chances of failures of IS development, and enhancing IS use through effective communication. Future research will delve into the development of agile methodologies and how they are currently incorporated in standards and bodies of knowledge related to software development. © 2025 The Authors.

关键词： Computer software selection and evaluation

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Analyzing Various Machine Learning Approaches for Detecting Android Malware

Analyzing Various Machine Learning Approaches for Detecting ...

引用

IEEE SoutheastCon conference on engineering the Future

作者： Dickey, Kyler Hwang, Doosung Kim, Donghoon Arkansas State Univ Dept Comp Sci Jonesboro AR 72401 USA Dankook Univ Dept Software Sci Yongin South Korea

ISBN: (纸本)9798350317107;9798350317114

The Android operating system is the world's largest smartphone platform. The platform carries with it significant risk due to the vast amounts of malware that target the platform. Newer methods involve the use of machine learning to detect malicious software in a more general manner, as opposed to conventional methods that rely on prior knowledge pertaining to a particular malware family. This study explores the use of a Convolutional Neural Network and various tree-based learning methods processing feature engineered from malware binaries. Overall model accuracy was found to be between 87% and 90%, and sufficient performance was obtained when collecting a certain amount of data above the threshold. It was also found that tuning some of the tree based model hyperparameters caused overfitting. Overall, the findings concluded that models that did not overfit performed comparably during both training and testing, representing consistent detection models.

关键词： Android malware machine learning features hyperparameter

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Context-Dependent Anomaly Detection with knowledge Graph Embedding Models 18

Context-Dependent Anomaly Detection with Knowledge Graph Emb...

引用

IEEE 18th International conference on Automation Science and engineering (IEEE CASE)

作者： Vaska, Nathan Leahy, Kevin Helus, Victoria MIT Lincoln Lab Lexington MA 02420 USA

ISBN: (数字)9781665490429

ISBN: (纸本)9781665490429

Increasing the semantic understanding and contextual awareness of machine learning models is important for improving robustness and reducing susceptibility to data shifts. In this work, we leverage contextual awareness for the anomaly detection problem. Although graphed-based anomaly detection has been widely studied, context-dependent anomaly detection is an open problem and without much current research. We develop a general framework for converting a context-dependent anomaly detection problem to a link prediction problem, allowing well-established techniques from this domain to be applied. We implement a system based on our framework that utilizes knowledge graph embedding models and demonstrates the ability to detect outliers using context provided by a semantic knowledge base. We show that our method can detect context-dependent anomalies with a high degree of accuracy and show that current object detectors can detect enough classes to provide the needed context to show good performance within our example domain.

关键词： knowledge engineering Computer aided software engineering Semantics knowledge based systems Machine learning Detectors Robustness

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Modeling Time Decay Effect in Temporal knowledge Graphs via Multivariate Hawkes Process

Modeling Time Decay Effect in Temporal Knowledge Graphs via ...

引用

International Joint conference on Neural Networks (IJCNN)

作者： Li, Qianyu Chen, Jiebin Tang, Xiaoli Yu, Han Song, Hengjie South China Univ Technol Sch Software Engn Guangzhou Peoples R China Nanyang Technol Univ Sch Comp Sci & Engn Singapore Singapore

ISBN: (纸本)9798350359329;9798350359312

knowledge Graph Embedding (KGE) is attracting growing research interest because it offers great flexibility for the manipulation and application of knowledge Graphs (KGs). However, most existing works focus on static KGE, while temporal KGE is still in its infancy. Recent temporal KGE methods attempt to obtain the long-term dependency of facts in consecutive timestamps by merging historical fact information. However, they ignore the different impacts of historical facts on the current facts due to the time decay effect and heterogeneity of historical facts. To bridge this gap, we formalize the concept of fact formation sequence to describe the evolution of an entity and propose the Modeling Time Decay Effect in Temporal knowledge Graphs via Multivariate Hawkes Process method (TimeDE). TimeDE uses the Hawkes process to model the time decay effect of historical facts. It also incorporates the attention mechanism based on the score function of static KGE methods to better capture the impacts of heterogeneous historical facts on the current facts. Extensive experiments on the five commonlyused benchmark datasets demonstrate that TimeDE achieves significant improvements in terms of both Mean Reciprocal Rank and Hits@K compared to state-of-the-art methods.

关键词： knowledge graph Graph embedding Hawkes process Attention mechanism

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The Recent Trends of Research on GitHub Copilot: A Systematic Review 9th

The Recent Trends of Research on GitHub Copilot: A Systemati...

引用

9th International conference on Computing and Informatics, ICOCI 2023

作者： Ani, Zhamri Che Hamid, Zauridah Abdul Zhamri, Nur Nazifa School of Computing University Utara Malaysia Kedah Sintok06010 Malaysia Sime Darby Motors Petaling Jaya47301 Malaysia

ISBN: (纸本)9789819995882

GitHub Copilot is an AI-powered code generation tool developed by OpenAI and GitHub that has gained significant attention from the software engineering community. Despite the significant attention received from the software engineering community, there is a lack of comprehensive examination of its effectiveness, reliability, and ethical implications on GitHub Copilot. The absence of a systematic review of GitHub Copilot's recent research trends hinders a thorough understanding of its current state of development and potential impact on software development practices. Therefore, this systematic review aims to analyze the recent trends of research on GitHub Copilot to assess its current state of development, identify gaps in existing knowledge, and provide insights into potential future research directions. This study used PRISMA for searching the relevant databases, screening and selecting eligible studies based on inclusion and exclusion criteria, data extraction and synthesis, and critical appraisal of the quality and relevance of the studies included. The results show that the trend of the studies is focusing on four main areas: developer productivity, code quality, code security and education. © 2024, The Author(s), under exclusive license to Springer Nature Singapore Pte Ltd.

关键词： software reliability

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A Study of the Accuracy of the software Site Survey to Find the Appropriate Location to Install the Access Point for Indoor Positioning 20

A Study of the Accuracy of the Software Site Survey to Find ...

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20th International conference on ICT and knowledge engineering (ICT and KE)

作者： Srikamta, Nimit Namee, Khanista Chatngoen, Korakod Boonkuson, Noppadon Meny, Areej Kaewsaeng-On, Rudsada King Mongkuts Univ Technol North Bangkok Fac Ind Technol & Management Bangkok Thailand King Saud Bin Abdulaziz Univ Hlth Sci Jeddah Saudi Arabia Prince Songkla Univ Hat Yai Thailand

ISBN: (数字)9781665486606

ISBN: (纸本)9781665486606

Currently, there are many researches trying to find the position of people inside the building or indoor positioning to apply in many different applications in the future. This research is an early stage, the idea is to find the location of people inside the building through the Wi-Fi signal from the access point. This paper will present the location to install the appropriate access point device inside the building to further develop the indoor positioning system. A comparative analysis of the access point's design and operation was performed using a software Heat Map Planner called Ruckus Wireless ZonePlanner, a software license from Ruckus, designed specifically for Wi-Fi systems and using software Site Surveys to collect data to verify the accuracy of the information. Three software site surveys, Wi-Fi Analyzer, Net Spot, and inSSIDer Home, were used to find average data collection. Then compare with the software Heat Map Planner to see how much signal quality deviation and signal quality is measured when the signal is broadcast through the walls of the building's infrastructure: concrete, brick walls, glass walls with metal frames. Summarize the results of each signal quality analysis, the signal quality is between -29 and -68 but based on actual measurements using 3 different software, the signal quality is between -29 and -74, the least error is 9 and the maximum is -28.

关键词： indoor positioning heat map Wi-Fi attenuation indoor location tracking

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