Titlebook: Artificial Intelligence. ECAI 2023 International Workshops; XAI^3, TACTIFUL, XI- S?awomir Nowaczyk,Przemys?aw Biecek,Vania Dimitrov Confere

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書目名稱Artificial Intelligence. ECAI 2023 International Workshops影響因子(影響力)

書目名稱Artificial Intelligence. ECAI 2023 International Workshops影響因子(影響力)學(xué)科排名

書目名稱Artificial Intelligence. ECAI 2023 International Workshops網(wǎng)絡(luò)公開度

書目名稱Artificial Intelligence. ECAI 2023 International Workshops網(wǎng)絡(luò)公開度學(xué)科排名

書目名稱Artificial Intelligence. ECAI 2023 International Workshops被引頻次

書目名稱Artificial Intelligence. ECAI 2023 International Workshops被引頻次學(xué)科排名

書目名稱Artificial Intelligence. ECAI 2023 International Workshops年度引用

書目名稱Artificial Intelligence. ECAI 2023 International Workshops年度引用學(xué)科排名

書目名稱Artificial Intelligence. ECAI 2023 International Workshops讀者反饋

書目名稱Artificial Intelligence. ECAI 2023 International Workshops讀者反饋學(xué)科排名

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Yaochu Jin,Hangyu Zhu,Yang Chennd cannot fully consider various dynamic features. In this paper, we propose a novel and generic method based on dynamic graph embedding and clustering. Inspired by the existing knowledge about dynamic opinion leader detection, the proposed method can exploit both the topological and temporal inform

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https://doi.org/10.1007/978-3-031-07838-5ta mining process. In many cases though, the resulting set of association rules is by far too big and confusing for a . to extract useful knowledge. Moreover, the domain expert might often expect that particular association rules are generated by the data mining process and would like to be able to

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