商学院:Research on Group Decision Support Systems: Large Groups, Consensus, and Multi-香港六合彩开奖结果|今日特码开什么|管家婆中特网

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文章摘要:商学院:Research on Group Decision Support Systems: Large Groups, Consensus, and Multi,看来,詹宁斯救世主的光环就要破灭了,他在预测本年度最佳新秀的榜单上,已经落后了国王的埃文斯。詹宁斯自己说他的得分下降,是因为当里德归来时,自己缺少了进攻的机会,现在里德又因为膝盖而离开的球场,可他今天8投1中只拿到了5分。比哈维大一岁的皮尔洛与哈维并为当今足坛的两大技术流后腰,犀利的伊涅斯塔和老道的里克尔梅更有千秋,图雷和加图索则是防守型后腰的新老两大代表。从名气和实力上看,两套阵容难分伯仲,但从默契程度和年龄节奏出发,巴萨明显占优。毕竟里克尔梅曾经历了一段黑暗的巴萨时光,与哈维完全找不到感觉的他能否与皮尔洛共存让人担忧,加图索则有32岁,很那指望这位老将延续跑不死的作风。意大利踢出了一场完美的比赛,其实这早有预兆,上场对罗马尼亚的平局,虽然几乎将他们逼到了绝境,但实际上他们踢得并不差,只怪没带因扎吉的他们射术太差。而法国不仅用人上问题重重,他们整场对于意大利的打中卫身后战术疲于奔命,而值得注意的是,速度是托尼的绝对劣势,意大利这场也只上了一个前锋。在阿比达尔下场之前,法国防线已极为吃紧,他最终被罚下也正式源自这种战术。这说明三个问题,法国中前场对对手逼抢不紧,屡屡让对手从容出球;中卫缺少身高,无法抢前点形成拦截;调整能力差,让对手几乎这么折腾了一晚上。这些问题的指向,则表明多梅内克确实不适合呆在法国队了。, 而麦迪,自然就是西天取经(夺取总冠军)的领导人唐僧。细皮嫩肉,招人喜欢,却又有点小胆怯,有点小忧郁,实在是唐僧的不二人选。而他的领导力,也是美国媒体所津津乐道的:08年,还曾因为在火箭时所展现的领导力,麦迪被列入常规赛MVP候选人第3位。而在中国数百媒体的长枪短炮下,在数亿球员的狂轰乱炸下,稳稳的压制姚明,当仁不让的成为火箭唯一核心,掌握最后一攻权利的麦迪,30岁,带着与生俱来的领导力,这绝对是上天赐给面临“一山二虎”的热火最佳的礼物。这次PK,有几大看点:一是国奥要报8月初“一箭之仇”,能否如愿?二是贾秀全当真是执掌国奥队的“最后一战”吗?这一战之后,杜伊随即走马上任,他将走向神坛,还是叩响恶梦之门?一场极为普通的足球比赛,却演绎成一次看不见的血雨腥风大博杀,这已经成了中国足球一条不变的定律。李玮峰+肇俊哲?08中超将铸就鲁能时代!。

时间:20171124日(周五)下午2:00-4:30

地点:博学楼A100

报告人:Iván Palomares Carrascosa

报告人介绍:Iván Palomares Carrascosa is a Lecturer in Computer Science with the School of Computer Science, Electrical and Electronic Engineering, and Engineering Maths (SCEEM), University of Bristol, and visiting Professor with the Management and Economics Sciences School, University of Occidente (Mexico). He received his MSc and PhD degrees (with nationwide distinctions) from the Universities of Granada and Jaén (Spain). Iván’s research interests include AI techniques to support decision making under uncertainty, consensus building, multi-view and collaborative filtering recommender systems, human-machine decision support, fuzzy preference aggregation and data fusion. Applications of his research include management, group recommender systems, disaster management, cybersecurity and energy planning. He has co-authored 13 publications in international journals and over 30 contributions to conferences, along with his recently published co-edited Springer book “Data Analytics and Decision Support for Cybersecurity”.

报告内容:Real-life collective decision making situations typically involve added complexities such as: (I) the need for effectively handling uncertainty due to human vagueness/subjectivity in expressing preferences; (II) the presence of multiple evaluation criteria and participants with diverse background, demanding appropriate preference aggregation methods; and importantly, (III) the importance of making consensual decisions. All the above challenges accentuate in large-group decision making problems involving a large amount of diverse participants, and in group recommender systems, in which an enormous number of items and user preferences must be analysed to recommend the best product or service to a group. Both situations have increasingly become a reality in recent years, due to the rise of social network and crowd-based platforms, along with the latest advances in mobile/cloud computing.

This talk firstly introduces the main challenges of large-group decision making problems, followed by an overview of recent research trends in the topic. Particular focus is given to consensus approaches to support accepted large-group decisions. Secondly, the talk introduces multi-view data approaches in recommender systems, outlining how aggregation techniques can be potentially utilized to intelligently incorporate multiple views of information and improve recommendation processes for groups of users. The talk concludes with a series of “lessons learnt” and future directions of research.

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