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书目名称Artificial Intelligence in HCI影响因子(影响力)<br> http://impactfactor.cn/if/?ISSN=BK0162462<br><br> <br><br>书目名称Artificial Intelligence in HCI影响因子(影响力)学科排名<br> http://impactfactor.cn/ifr/?ISSN=BK0162462<br><br> <br><br>书目名称Artificial Intelligence in HCI网络公开度<br> http://impactfactor.cn/at/?ISSN=BK0162462<br><br> <br><br>书目名称Artificial Intelligence in HCI网络公开度学科排名<br> http://impactfactor.cn/atr/?ISSN=BK0162462<br><br> <br><br>书目名称Artificial Intelligence in HCI被引频次<br> http://impactfactor.cn/tc/?ISSN=BK0162462<br><br> <br><br>书目名称Artificial Intelligence in HCI被引频次学科排名<br> http://impactfactor.cn/tcr/?ISSN=BK0162462<br><br> <br><br>书目名称Artificial Intelligence in HCI年度引用<br> http://impactfactor.cn/ii/?ISSN=BK0162462<br><br> <br><br>书目名称Artificial Intelligence in HCI年度引用学科排名<br> http://impactfactor.cn/iir/?ISSN=BK0162462<br><br> <br><br>书目名称Artificial Intelligence in HCI读者反馈<br> http://impactfactor.cn/5y/?ISSN=BK0162462<br><br> <br><br>书目名称Artificial Intelligence in HCI读者反馈学科排名<br> http://impactfactor.cn/5yr/?ISSN=BK0162462<br><br> <br><br>
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发表于 2025-3-22 22:13:20
ExMo: ,plainable AI ,del Using Inverse Frequency Decision Rules a qualitatively better model than BRL. Furthermore, ExMo demonstrates that the textual explanation can be provided in a human-friendly way so that the explanation can be easily understood by non-expert users. We validate ExMo on several datasets with different sizes to evaluate its efficacy. Experi
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发表于 2025-3-23 02:56:27
A Model of Adaptive Gamification in Collaborative Location-Based Collecting Systemsnsidering the space-time behavior and challenge completion, a model for the different types of challenges applicable in CLCS, a model for the CLCS objectives and coverage, and a strategy for the application of Machine Learning techniques for adaptation.
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发表于 2025-3-23 06:47:05
Benchmarking Neural Networks-Based Approaches for Predicting Visual Perception of User Interfaceslity of CNN (a modified GoogLeNet architecture) and ANN models to predict visual perception per Aesthetics, Complexity, and Orderliness scales for about 2700 web UIs assessed by 137 users. Our results suggest that the ANN architecture produces smaller Mean Squared Error (MSE) for the training datase