Circumscribe 发表于 2025-3-23 10:05:53
http://reply.papertrans.cn/16/1513/151236/151236_11.pngAlbumin 发表于 2025-3-23 16:24:50
http://reply.papertrans.cn/16/1513/151236/151236_12.png宽容 发表于 2025-3-23 20:24:45
Gulsan Karbani,Susie Godsil,Robert MuellerX models based on the outcome variables that are of interest in terms of explanation or prediction. At the same time, there is potential for (partial) re-using UX models across products and generalisation of models. As a case study, an experience model is developed for a particular consumer product,interrupt 发表于 2025-3-24 01:52:33
Josephine Green,Merry France-Dawson each other to improve their learning ability. This paper focuses on association rule, and presents MALA, a model for argumentation based multi-agent joint learning which integrates ideas from machine learning, data mining and argumentation. We introduce the argumentation model Arena as a communicat新星 发表于 2025-3-24 05:03:51
http://reply.papertrans.cn/16/1513/151236/151236_15.png形上升才刺激 发表于 2025-3-24 09:51:55
Jennifer Kromberg,Trefor Jenkinspammer detection and other fields. We focus on the features of authors behavior on the dynamic data. This paper applies multi-agent system to the authors information mining fields and proposes a recognition model based on multi-agent system: MVIA-MAS. We cluster the author information in each time s热情的我 发表于 2025-3-24 14:24:12
http://reply.papertrans.cn/16/1513/151236/151236_17.pngBone-Scan 发表于 2025-3-24 16:44:14
https://doi.org/10.1007/978-3-031-37530-9ices) such as Facebook, more and more people are attracted to Internet. Internet provides many benefits to people, but yields a consequent disturbing phenomenon of obsession with Internet, which is called PIU (Pathological Internet Use) or IAD (Internet Addiction Disorder) in academia. PIU or IAD ha抵消 发表于 2025-3-24 22:36:01
http://reply.papertrans.cn/16/1513/151236/151236_19.png头脑冷静 发表于 2025-3-25 01:05:21
https://doi.org/10.1007/978-3-031-37530-9idemiology and recommendation systems. In particular, information cascades can be useful for not only inferring the underlying structure of the network, but also providing insights on the properties of information itself. In this paper, we address the problem of jointly modeling the influence struct