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检索条件"机构=Sichuan Key Laboratory of Software Automatic Generation and Intelligent Service"

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Knowledge graph question answering system based on code defect 3

Knowledge graph question answering system based on code defe...

引用

3rd International Conference on Computer Science and Management Technology, ICCSMT 2022

作者： He, Yang Wei, Le Chengdu University of Information Technology School of Software Engineering Sichuan Chengdu China Automatic Software Generation & Intelligence Service Key Laboratory of Sichuan Province Sichuan Chengdu China

ISBN: (纸本)9798350320404

In the current scenario of code defect aided search, the code defect knowledge is not accurate enough due to the singularity and island of code defect knowledge, so that developers and testers can not accurately use the defect knowledge. To solve this problem, this paper proposes a question answering system construction method based on code defect knowledge graph. Firstly, a large number of code defect knowledge is cleaned to obtain the entities and relationships of code defect knowledge, and the corresponding code defect knowledge graph is established. Then the combination of Bert model and Prompt makes the system better identify user intentions. The effectiveness of this method is verified based on the accuracy comparison with the commonly used models in this field. Experiments show that the combination of Bert model and Prompt makes this method more accurate in identifying user intention. © 2022 IEEE.

关键词： Knowledge graph

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Improvement of Federal Average Algorithm Based on CRITIC Weighting Method 2

Improvement of Federal Average Algorithm Based on CRITIC Wei...

引用

2nd International Conference on Artificial Intelligence and intelligent Information Processing, AIIIP 2023

作者： Yu, Qiantong Wei, Nianqing Mi, Yiyang College of Software Chengdu University of Information Technology Chengdu610225 China Sichuan Province Chengdu University of Information Technology Key Laboratory of Software Automatic Generation and Intelligent Service Chengdu610225 China

ISBN: (纸本)9798350371451

Federated learning is a machine learning technology that can protect data privacy. Its federated average algorithm updates the global model through weights. In view of the influence of subjective factors in the calculation of data weights by analytic hierarchy process (AHP), a federated average algorithm based on CRITIC weighting method is proposed to process multi-source data from the perspective of data diversity and volatility. In the experiment, the CRITIC weighting method is used to calculate the importance of each attribute in the data, and it is used as the model aggregation parameter to calculate the weight of each client data. By applying the federated average algorithm in horizontal federated learning to the data model training fusion, the accuracy of data model establishment is improved. In terms of both theoretical basis and practical research, experiments and analysis on the collected data sets show that the proposed method is executable. The experimental results show that the proposed method improves the accuracy by about 4 % compared with the federal average algorithm, reduces the communication overhead of the federal learning and training process, and improves the overall efficiency. © 2023 IEEE.

关键词： Analytic hierarchy process

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Adaptive Effect Evaluation Model of Composite Cloud service in Cloud Manufacturing Environment 6

Adaptive Effect Evaluation Model of Composite Cloud Service ...

引用

6th IEEE International Conference on Computer and Communications, ICCC 2020

作者： Wei, Le Zhao, Qiuyun Chang, Yu Shu, Hongping School of Software Engineering Chengdu University of Information Technology Chengdu China Automatic Software Generation and Intelligence Service Key Laboratory of Sichuan Province Chengdu China

ISBN: (纸本)9781728186351

Composite cloud service adaptive adjustment is an important means to achieve the flexibility of manufacturing cloud service composite flexibility. In order to evaluate the adaptive adjustment effect of composite cloud services and ensure the smooth progress of manufacturing activities, an adaptive effect evaluation model of composite cloud services is proposed. The model adopts a post-evaluation method, taking the user satisfaction, product qualification rate, operational stability, cost, time, and the QoS distance as evaluation indicators. The comprehensive evaluation value is obtained through the weighted sum of each index, avoiding the evaluation distortion caused by a single indicator. The evaluation framework and evaluation algorithm of the adaptive effect evaluation model are given. Combined with examples, the method can reflect the real situation better, and has practical operability. © 2020 IEEE.

关键词： Distributed database systems

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An Information Perception Model in Cloud Manufacturing Environment for Manufacturing Task Execution 6

An Information Perception Model in Cloud Manufacturing Envir...

引用

6th IEEE International Conference on Computer and Communications, ICCC 2020

作者： Zhao, Qiuyun Wei, Le Shu, Hongping School of Software Engineering Chengdu University of Information Technology Chengdu China Automatic Software Generation and Intelligence Service Key Laboratory of Sichuan Province Chengdu China

ISBN: (纸本)9781728186351

Aiming at the problem of information perception in cloud manufacturing environment, this paper proposed a information perception model in cloud manufacturing environment for manufacturing task execution. This model takes manufacturing task execution as the core, and gets cloud manufacturing environment information from the environment of the cloud manufacturing operation platform, physical locations of manufacturing tasks, manufacturing tasks and other cloud services closely related to manufacturing tasks. The information includes the equipment, logistics, human resources, perception capabilities, and maintenance capabilities. Different environment information is perceived by sensors, software agents, GPS, man-machine interfaces and system interaction interfaces. The perceived information would be transformed into events and then merged together. The model realized algorithms of the event transformation and the key event identification. The example analysis shows that the model can acquire changes of cloud manufacturing environment information in time and ensure the execution of manufacturing tasks smoothly. © 2020 IEEE.

关键词： software agents

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Cloud service selection method based on overall similarity in cloud manufacturing environment

Cloud service selection method based on overall similarity i...

引用

2021 IEEE International Conference on Artificial Intelligence and Industrial Design, AIID 2021

作者： Liao, Wenli Wei, Le School of Software Engineering Chengdu University of Information Technology Chengdu China Automatic Software Generation and Intelligence Service Key Laboratory of Sichuan Province Chengdu China

ISBN: (纸本)9780738110837

The physical location of manufacturing services cannot be considered well in cloud service selection. In order to solve this problem, a cloud service selection considering the physical location of the manufacturing service is proposed. First, the cloud manufacturing service is described. Second, the type, functional attributes, physical location and service QoS are considered, and manufacturing service chain is formed according to manufacturing task flow. Finally, thresholds and weights are designed by combining four similarity algorithms to narrow the scope of result set and improve accuracy. The analysis of numerical examples shows, this method can narrow the selection range, and ensure that the selected manufacturing services and manufacturing tasks have a high degree of similarity. © 2021 IEEE.

关键词： Numerical methods

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An Event-driven Adaptive Strategy for Manufacturing Cloud services

An Event-driven Adaptive Strategy for Manufacturing Cloud Se...

引用

2020 International Conference on Engineering Management of Communication and Technology, EMCTECH 2020

作者： Wei, Le Wang, Ruixiang Zhao, Qiuyun Shu, Hongping School of Software Engineering Chengdu University of Information Technology Chengdu China Laboratory of Sichuan Province Automatic Software Generation and Intelligence Service Key Chengdu China

ISBN: (纸本)9781665404488

In order to ensure the progress of manufacturing tasks smoothly in cloud manufacturing environment, an event-driven adaptive strategy have been proposed for manufacturing cloud services. For the execution of manufacturing tasks and virtual manufacturing units, events that trigger adaptive actions of manufacturing cloud services were divided into three categories of environment, manufacturing tasks and cloud services. There 19 types in detail. An event-driven manufacturing cloud service adaptive model was established. The processing algorithms of different events were given. Combined with an example, the process of event processing was described, and the model and algorithm were verified. Results show that the adaptive strategy can obviously guarantee the development of manufacturing activities in cloud manufacturing environment. © 2020 IEEE.

关键词： Web services

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A Semantic Code Search Method Based on Program Conversion 2

A Semantic Code Search Method Based on Program Conversion

引用

2nd International Conference on Algorithms, High Performance Computing and Artificial Intelligence, AHPCAI 2022

作者： Tao, Yan Wei, Le Shu, Hongping School of Software Engineering Chengdu University of Information Technology Sichuan Chengdu610225 China Automatic Software Generation & Intelligence Service Key Laboratory of Sichuan Province Chengdu610225 China

Aiming at the problem that code fragments can’t be captured accurately and quickly due to ignoring semantic information and structural information of source code in code search task, A semantic code search method based on program conversion is proposed (Semantic Code Search based on Program Conversion, SCSPC). The SCSPC diversified the data of the acquired code fragments through data enhancement, changed the program through variable renaming, exchanging two independent statements, circular exchange, inserting exception capture and if equivalent replacing switch statement, and trained the CodeBERT model with mixed objective functions (masking language modeling and replacing token detection) to generate sentence vectors with rich semantics for the code fragments and natural languages, and compared the similarity of the vectors to complete the code search. Experimental results show that compared with SWIM, QECK and CODEnn models, the average reciprocal ranking and hit rate (S@10) of SCSPC method are increased by 2% and 0.041 respectively. © 2022 Copyright for this paper by its authors. Use permitted under Creative Commons License Attribution 4.0 International (CC BY 4.0).

关键词： Semantics

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Enhanced sparse based discriminative topic representation for text categorization 6

Enhanced sparse based discriminative topic representation fo...

引用

6th International Conference on Systems and Informatics, ICSAI 2019

作者： Zheng, Wenbin Zhang, Wenxu Yue, Xi Gao, Yan Tang, Hong College of Software Engineering Chengdu University of Information Technology Chengdu610225 China Software Automatic Generation and Intelligent Service Key Laboratory of SiChuan Province Chengdu610225 China College of Engineering Sichuan Normal University Chengdu610068 China

ISBN: (纸本)9781728152561

This paper presents an enhanced sparse based discriminative topic representation method for text categorization. By constructing category center vectors and combining with the latent Dirichlet allocation model, a more discriminative dictionary is obtained, which can describe the relationship between topic and word well. Furthermore, an enhanced sparse representation of documents can be generated with a L1/2 regularization in order to achive a good relationship between document and topic. The experimental results show that our proposed approach achieves more stable classification performance and obtains more high sparse degree. © 2019 IEEE.

关键词： Statistics

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Fusion of Contrastive Learning and Heterogeneous Graph for Code Summarization 3

Fusion of Contrastive Learning and Heterogeneous Graph for C...

引用

3rd International Conference on Electronics and Information Technology, EIT 2024

作者： Zhong, Caiting Wei, Le Chengdu University of Information Technology School of Software Engineering Chengdu China Automatic Software Generation & Intelligence Service Key Laboratory of Sichuan Province Sichuan Manufacturing Information Industry Collaborative Innovation Center Chengdu China

ISBN: (纸本)9798350369151

Aiming at the shortcomings of existing code summary generation methods in dealing with the semantic complexity, structural diversity of code and the fusion of search summary and generation summary, a code summary generation method combining contrast learning and heterogeneous graph is proposed. Firstly, a dense vector retrieval framework based on double encoders is adopted to enhance the retrieval accuracy and semantic diversity of large-scale code data. Secondly, the abstract syntax tree is reconstructed into a heterogeneous graph. By introducing various node and edge types, the model's ability to capture complex semantic relationships between different node and edge types is deepened. Finally, the copy gate mechanism is introduced to realize the dynamic fusion of retrieval abstracts and generated model output in semantic level, which guarantees the semantic accuracy and relevance of generated abstracts. Experimental results confirm the effectiveness of this approach in improving the precision and relevance of generated code summaries. © 2024 IEEE.

关键词： Contrastive Learning

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A weakly supervised back-labeling-based method for named entity recognition in automotive manufacturing: MBIC-NER 3

A weakly supervised back-labeling-based method for named ent...

引用

3rd International Conference on Electronics and Information Technology, EIT 2024

作者： Yang, Heyu Wei, Le Chengdu University of Information Technology School of Software Engineering Chengdu China Automatic Software Generation & Intelligence Service Key Laboratory of Sichuan Province Sichuan Manufacturing Information Industry Collaborative Innovation Center Chengdu China

ISBN: (纸本)9798350369151

Aiming at the problems of lack of corpus, lack of entity annotation dataset and fragmented data in named entity recognition in the automobile manufacturing field, a new named entity recognition method is proposed: MBIC-NER. The method firstly constructs an automobile manufacturing annotation dataset by using the idea of weakly supervised back annotation, and generates word vector sequences of the input sentences by using MacBERT pre-training model in order to better understand the context and semantic associations, and improves the accuracy and effect of text processing in the field of automobile manufacturing;Secondly, BiLSTM model and IDCNN model are constructed to perform feature extraction on the input word vector sequences to form a multilevel feature representation;Finally, the character sequences are continued to be decoded through the CRF, and the corresponding label of each character is obtained. The result show that the F1-score of MBIC-NER for named entity recognition in the self-constructed automobile manufacturing domain dataset reaches 87.03%, which is better than the other named entity recognition methods in comparison. © 2024 IEEE.

关键词： Semantics

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