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Titlebook: Advanced Information Systems Engineering; 34th International C Xavier Franch,Geert Poels,Monique Snoeck Conference proceedings 2022 Springe

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發(fā)表于 2025-3-21 18:04:49 | 只看該作者 |倒序?yàn)g覽 |閱讀模式
期刊全稱Advanced Information Systems Engineering
期刊簡(jiǎn)稱34th International C
影響因子2023Xavier Franch,Geert Poels,Monique Snoeck
視頻videohttp://file.papertrans.cn/146/145731/145731.mp4
學(xué)科分類Lecture Notes in Computer Science
圖書封面Titlebook: Advanced Information Systems Engineering; 34th International C Xavier Franch,Geert Poels,Monique Snoeck Conference proceedings 2022 Springe
影響因子This book constitutes the refereed proceedings of the 34th International Conference on Advanced Information Systems Engineering, CAiSE 2022, which was held in Leuven, Belgium, during June 6-10, 2022..The 31 full papers included in these proceedings were selected from 203 submissions. They were organized in topical sections as follows: Process mining; sustainable and explainable applications; tools and methods to support research and design; process modeling; natural language processing techniques in IS engineering; process monitoring and simulation; graph and network models; model analysis and comprehension; recommender systems; conceptual models, metamodels and taxonomies; and services engineering and digitalization..
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書目名稱Advanced Information Systems Engineering影響因子(影響力)




書目名稱Advanced Information Systems Engineering影響因子(影響力)學(xué)科排名




書目名稱Advanced Information Systems Engineering網(wǎng)絡(luò)公開度




書目名稱Advanced Information Systems Engineering網(wǎng)絡(luò)公開度學(xué)科排名




書目名稱Advanced Information Systems Engineering被引頻次




書目名稱Advanced Information Systems Engineering被引頻次學(xué)科排名




書目名稱Advanced Information Systems Engineering年度引用




書目名稱Advanced Information Systems Engineering年度引用學(xué)科排名




書目名稱Advanced Information Systems Engineering讀者反饋




書目名稱Advanced Information Systems Engineering讀者反饋學(xué)科排名




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Conference proceedings 2022ss modeling; natural language processing techniques in IS engineering; process monitoring and simulation; graph and network models; model analysis and comprehension; recommender systems; conceptual models, metamodels and taxonomies; and services engineering and digitalization..
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Albert Evrard sj,Clémence Lacourtracted using existing NLP and ML techniques and (ii) contextual knowledge to capture the different classes of complex intents. We devise a context knowledge service to capture the requisite contextual knowledge.
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Service Placement and Managements analysis and optimization. So far, decision discovery has been merely based on data elements that are measured at a single point in time. However, as cases from different application areas show, process behavior and process outcomes might be heavily influenced by additional data such as sensor str
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