Pub Date : 2024-02-23DOI: 10.1142/s0218194024500062
Nguyen Hung-Cuong, Huynh Quyet-Thang
{"title":"An imperfect debugging non-homogeneous Poisson process software reliability model based on a 3-parameter S-shaped function","authors":"Nguyen Hung-Cuong, Huynh Quyet-Thang","doi":"10.1142/s0218194024500062","DOIUrl":"https://doi.org/10.1142/s0218194024500062","url":null,"abstract":"","PeriodicalId":50288,"journal":{"name":"International Journal of Software Engineering and Knowledge Engineering","volume":null,"pages":null},"PeriodicalIF":0.9,"publicationDate":"2024-02-23","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"140436674","PeriodicalName":null,"FirstCategoryId":null,"ListUrlMain":null,"RegionNum":4,"RegionCategory":"计算机科学","ArticlePicture":[],"TitleCN":null,"AbstractTextCN":null,"PMCID":"","EPubDate":null,"PubModel":null,"JCR":null,"JCRName":null,"Score":null,"Total":0}
Pub Date : 2024-02-16DOI: 10.1142/s0218194024400011
Xiao Wei, Yidian Lin, Qitao Hu
{"title":"Dialogue Generation Model with Hierarchical Encoding and Semantic Segmentation of Dialogue Context","authors":"Xiao Wei, Yidian Lin, Qitao Hu","doi":"10.1142/s0218194024400011","DOIUrl":"https://doi.org/10.1142/s0218194024400011","url":null,"abstract":"","PeriodicalId":50288,"journal":{"name":"International Journal of Software Engineering and Knowledge Engineering","volume":null,"pages":null},"PeriodicalIF":0.9,"publicationDate":"2024-02-16","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"139961314","PeriodicalName":null,"FirstCategoryId":null,"ListUrlMain":null,"RegionNum":4,"RegionCategory":"计算机科学","ArticlePicture":[],"TitleCN":null,"AbstractTextCN":null,"PMCID":"","EPubDate":null,"PubModel":null,"JCR":null,"JCRName":null,"Score":null,"Total":0}
Pub Date : 2024-02-16DOI: 10.1142/s0218194024500050
Xiaowei Zhang, Zhifei Chen, Yulu Cao, Lin Chen, Yuming Zhou
{"title":"Multi-Intent Inline Code Comment Generation via Large Language Model","authors":"Xiaowei Zhang, Zhifei Chen, Yulu Cao, Lin Chen, Yuming Zhou","doi":"10.1142/s0218194024500050","DOIUrl":"https://doi.org/10.1142/s0218194024500050","url":null,"abstract":"","PeriodicalId":50288,"journal":{"name":"International Journal of Software Engineering and Knowledge Engineering","volume":null,"pages":null},"PeriodicalIF":0.9,"publicationDate":"2024-02-16","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"139962456","PeriodicalName":null,"FirstCategoryId":null,"ListUrlMain":null,"RegionNum":4,"RegionCategory":"计算机科学","ArticlePicture":[],"TitleCN":null,"AbstractTextCN":null,"PMCID":"","EPubDate":null,"PubModel":null,"JCR":null,"JCRName":null,"Score":null,"Total":0}
Pub Date : 2023-12-28DOI: 10.1142/s0218194023420019
Weidong Liu, Fei Li, Senjun Pei, Chunming Cheng
With the increasing number of patent applications over the years, instances of patent infringement cases have become more frequent. However, traditional manual patent infringement detection models are no longer suitable for large-scale infringement detection. Existing automated models mainly focus on detecting one-to-one patent infringements, but neglect the many-to-one scenarios. The many-to-one patent infringement detection model faces some major challenges. First, the diversity of patent domains, complexity of content and ambiguity of features make it difficult to extract and represent patent features. Second, patent infringement detection relies on the correlation between patents and the comparison of contextual information as the key factors, but modeling the process and drawing conclusions present challenges. To address these challenges, we propose a many-to-one patent graph (MPG) embedding base infringement detection model. Our model extracts the relationship between keywords and patents, as well as association relation between keywords from many-to-one patent texts (MPTs), to construct a MPG. We obtain patent infringement features through graph embedding of MPG. By using these embedding features as input, the many-to-one infringement detection (MOID) model outputs the conclusion on whether a patent is infringed or not. The comparative experimental results indicate that our model improves accuracy, precision and F-measure by 3.81%, 11.82% and 5.37%, respectively, when compared to the state-of-the-art method.
{"title":"MOID: Many-to-One Patent Graph Embedding Base Infringement Detection Model","authors":"Weidong Liu, Fei Li, Senjun Pei, Chunming Cheng","doi":"10.1142/s0218194023420019","DOIUrl":"https://doi.org/10.1142/s0218194023420019","url":null,"abstract":"<p>With the increasing number of patent applications over the years, instances of patent infringement cases have become more frequent. However, traditional manual patent infringement detection models are no longer suitable for large-scale infringement detection. Existing automated models mainly focus on detecting one-to-one patent infringements, but neglect the many-to-one scenarios. The many-to-one patent infringement detection model faces some major challenges. First, the diversity of patent domains, complexity of content and ambiguity of features make it difficult to extract and represent patent features. Second, patent infringement detection relies on the correlation between patents and the comparison of contextual information as the key factors, but modeling the process and drawing conclusions present challenges. To address these challenges, we propose a many-to-one patent graph (MPG) embedding base infringement detection model. Our model extracts the relationship between keywords and patents, as well as association relation between keywords from many-to-one patent texts (MPTs), to construct a MPG. We obtain patent infringement features through graph embedding of MPG. By using these embedding features as input, the many-to-one infringement detection (MOID) model outputs the conclusion on whether a patent is infringed or not. The comparative experimental results indicate that our model improves accuracy, precision and F-measure by 3.81%, 11.82% and 5.37%, respectively, when compared to the state-of-the-art method.</p>","PeriodicalId":50288,"journal":{"name":"International Journal of Software Engineering and Knowledge Engineering","volume":null,"pages":null},"PeriodicalIF":0.9,"publicationDate":"2023-12-28","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"140170226","PeriodicalName":null,"FirstCategoryId":null,"ListUrlMain":null,"RegionNum":4,"RegionCategory":"计算机科学","ArticlePicture":[],"TitleCN":null,"AbstractTextCN":null,"PMCID":"","EPubDate":null,"PubModel":null,"JCR":null,"JCRName":null,"Score":null,"Total":0}
Pub Date : 2023-12-14DOI: 10.1142/s0218194023500699
Naglaa A. Eldanasory, Engy Yehia, A. Idrees
{"title":"EFSP: an enhanced full scrum process model","authors":"Naglaa A. Eldanasory, Engy Yehia, A. Idrees","doi":"10.1142/s0218194023500699","DOIUrl":"https://doi.org/10.1142/s0218194023500699","url":null,"abstract":"","PeriodicalId":50288,"journal":{"name":"International Journal of Software Engineering and Knowledge Engineering","volume":null,"pages":null},"PeriodicalIF":0.9,"publicationDate":"2023-12-14","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"138971555","PeriodicalName":null,"FirstCategoryId":null,"ListUrlMain":null,"RegionNum":4,"RegionCategory":"计算机科学","ArticlePicture":[],"TitleCN":null,"AbstractTextCN":null,"PMCID":"","EPubDate":null,"PubModel":null,"JCR":null,"JCRName":null,"Score":null,"Total":0}
Pub Date : 2023-12-14DOI: 10.1142/s0218194023500687
Yasir Hussain, Zhiqiu Huang, Yu Zhou, I. A. Khan
{"title":"Exploring the Impact of Vocabulary Techniques on Code Completion: A Comparative Approach","authors":"Yasir Hussain, Zhiqiu Huang, Yu Zhou, I. A. Khan","doi":"10.1142/s0218194023500687","DOIUrl":"https://doi.org/10.1142/s0218194023500687","url":null,"abstract":"","PeriodicalId":50288,"journal":{"name":"International Journal of Software Engineering and Knowledge Engineering","volume":null,"pages":null},"PeriodicalIF":0.9,"publicationDate":"2023-12-14","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"138973276","PeriodicalName":null,"FirstCategoryId":null,"ListUrlMain":null,"RegionNum":4,"RegionCategory":"计算机科学","ArticlePicture":[],"TitleCN":null,"AbstractTextCN":null,"PMCID":"","EPubDate":null,"PubModel":null,"JCR":null,"JCRName":null,"Score":null,"Total":0}
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