International Conference on Behavioral, Economic, and Socio-Cultural Computing最新文献

Computational network science: From data to social models 计算网络科学:从数据到社会模型

International Conference on Behavioral, Economic, and Socio-Cultural Computing Pub Date : 2017-10-01 DOI: 10.1109/BESC.2017.8256355

Przemyslaw Kazienko

引用次数: 0

Ethics by reasoning in socio-technical and cognitive systems 在社会技术和认知系统中的推理伦理

International Conference on Behavioral, Economic, and Socio-Cultural Computing Pub Date : 2017-10-01 DOI: 10.1109/BESC.2017.8256354

O. Boissier

{"title":"Ethics by reasoning in socio-technical and cognitive systems","authors":"O. Boissier","doi":"10.1109/BESC.2017.8256354","DOIUrl":"https://doi.org/10.1109/BESC.2017.8256354","url":null,"abstract":"Socio-technical systems bring together the social and physical worlds where people, things and services interact altogether. With the development of Artificial Intelligence, these systems are increasingly incorporating automated cognitive processes, which are delegated to autonomous services and things acting on behalf of humans. The ever enlarging scope of activity of these systems raises many challenging issues, among which Ethics appears as crucial and is strongly discussed. In this talk, we present the current landscape of approaches and challenges related to the development of socio-technical and cognitive systems with ethical behaviors. We focus on models and technics to program such systems based on collective autonomous agents that are able to reason at the individual, social and collective levels on the ethical dimensions of their behaviors. This work is part of the ETHICAA project funded by the French National Agency for Research (ANR). In this project, Philosophers, Economists, Robotic and AI scholars develop models and a methodological framework in which to lay out the development of Ethics by Reasoning in Multi-Agent in Systems.","PeriodicalId":108957,"journal":{"name":"International Conference on Behavioral, Economic, and Socio-Cultural Computing","volume":"1 1","pages":"0"},"PeriodicalIF":0.0,"publicationDate":"2017-10-01","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"129362334","PeriodicalName":null,"FirstCategoryId":null,"ListUrlMain":null,"RegionNum":0,"RegionCategory":"","ArticlePicture":[],"TitleCN":null,"AbstractTextCN":null,"PMCID":"","EPubDate":null,"PubModel":null,"JCR":null,"JCRName":null,"Score":null,"Total":0}

引用次数: 2

DSAA/BESC Keynote Speeches: BigData, AllData, Old Data: Predictive analytics in a changing data landscape DSAA/BESC主题演讲:大数据、全数据、旧数据:数据环境变化中的预测分析

International Conference on Behavioral, Economic, and Socio-Cultural Computing Pub Date : 2014-10-01 DOI: 10.1109/BESC.2014.7059494

U. Fayyad

引用次数: 0

Friend recommendation of microblog in classification framework: Using multiple social behavior features 分类框架下的微博好友推荐:利用多社会行为特征

International Conference on Behavioral, Economic, and Socio-Cultural Computing Pub Date : 1900-01-01 DOI: 10.1109/BESC.2014.7059527

Siyao Han, Yan Xu

{"title":"Friend recommendation of microblog in classification framework: Using multiple social behavior features","authors":"Siyao Han, Yan Xu","doi":"10.1109/BESC.2014.7059527","DOIUrl":"https://doi.org/10.1109/BESC.2014.7059527","url":null,"abstract":"In recent years, microblog has been experiencing an explosive growth, which brings much inconvenience to users to build a healthy social circle in this chaos online world. Friend recommendation can automatically recommend potential friends, filter out the useless information, and facilitate the healthy development of social network. A novel friend recommendation approach is proposed in this paper. First, three kinds of social behavior features, i.e., social rating feature, social content features and social relation features, are extracted to represent the relationship of each user pair in the large-scale microblog data. Based on these features, a binary classifier is trained to determine whether the second user in each pair should be recommended to the first one. In this way, the original recommendation problem is transformed to a binary classification problem so that the sparseness problem of collaborative filtering method can be solved properly. Experiments shows that our approach improves the performance of friend recommendation compared with the traditional collaborative filtering methods.","PeriodicalId":108957,"journal":{"name":"International Conference on Behavioral, Economic, and Socio-Cultural Computing","volume":"1 1","pages":"0"},"PeriodicalIF":0.0,"publicationDate":"1900-01-01","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"116535845","PeriodicalName":null,"FirstCategoryId":null,"ListUrlMain":null,"RegionNum":0,"RegionCategory":"","ArticlePicture":[],"TitleCN":null,"AbstractTextCN":null,"PMCID":"","EPubDate":null,"PubModel":null,"JCR":null,"JCRName":null,"Score":null,"Total":0}

引用次数: 11

Chinese Zero Pronoun Resolution Based on Biaffine Attention Mechanism 基于双碱注意机制的汉语零代词消解

International Conference on Behavioral, Economic, and Socio-Cultural Computing Pub Date : 1900-01-01 DOI: 10.1109/BESC51023.2020.9348304

Likai Wang, Weiguang Qu, Tinxin Wei, Junsheng Zhou, Yanhui Gu, Bin Li

引用次数: 0