找回密码
 To register

QQ登录

只需一步,快速开始

扫一扫,访问微社区

Titlebook: Highlights in Practical Applications of Agents, Multi-Agent Systems, and Social Good. The PAAMS Coll; International Worksh Fernando De La P

[复制链接]
楼主: 无力向前
发表于 2025-3-28 17:33:08 | 显示全部楼层
发表于 2025-3-28 20:08:16 | 显示全部楼层
发表于 2025-3-29 02:50:13 | 显示全部楼层
Conference proceedings 2021-Agent Systems, PAAMS 2021, held in Salamanca, Spain, in October 2021..The total of 17 full and 9 short papers presented in this volume were carefully selected from 42 submissions..The papers in this volume stem from the following meetings:Workshop on Character Computing (C2); Workshop on Deep Learn
发表于 2025-3-29 06:40:26 | 显示全部楼层
发表于 2025-3-29 10:41:13 | 显示全部楼层
A Hybrid Supervised/Unsupervised Machine Learning Approach to Classify Web Servicesmerative hierarchical clustering algorithm. Second, several supervised learning algorithms have been applied to determine service categories. The findings show that the hybrid approach using the combination of hierarchical clustering and SVM provides acceptable results in comparison with other unsupervised/supervised combinations.
发表于 2025-3-29 13:01:12 | 显示全部楼层
发表于 2025-3-29 17:07:38 | 显示全部楼层
XReC: Towards a Generic Module-Based Framework for Explainable Recommendation Based on Charactery after the outbreak of the COVID-19, people head to the virtual world by shopping online instead of going to the actual store, watching movies on platforms like “Netflix” instead of going to cinemas, or companies are applying different methods to continue their internal operations online. So most c
发表于 2025-3-29 20:10:26 | 显示全部楼层
发表于 2025-3-30 01:51:29 | 显示全部楼层
Contributions of Character Computing to AI Based Adaptive Learning Environments – A Discussion which can be exploited for personalized learning using AI based approaches of XAI and active learning. Integrating concepts of character computing enables a more robust adaptation to the learner’s needs. The paper discusses future application scenarios of XAI, virtual learning companions and social
发表于 2025-3-30 07:18:18 | 显示全部楼层
An Attentional Model for Earthquake Prediction Using Seismic Datae; therefore, techniques to predict such events are essential to minimize their impacts. However, despite all efforts to estimate the occurrence of a disaster, making an accurate and robust forecast is a challenging task. In recent years, Deep Learning techniques have innovated several fields by lea
 关于派博传思  派博传思旗下网站  友情链接
派博传思介绍 公司地理位置 论文服务流程 影响因子官网 SITEMAP 大讲堂 北京大学 Oxford Uni. Harvard Uni.
发展历史沿革 期刊点评 投稿经验总结 SCIENCEGARD IMPACTFACTOR 派博系数 清华大学 Yale Uni. Stanford Uni.
|Archiver|手机版|小黑屋| 派博传思国际 ( 京公网安备110108008328) GMT+8, 2025-5-2 20:53
Copyright © 2001-2015 派博传思   京公网安备110108008328 版权所有 All rights reserved
快速回复 返回顶部 返回列表