2020 7th International Conference on Behavioural and Social Computing (BESC)最新文献

MHIVis: Visual Analytics for Exploring Mental Illness of Policyholders in Life Insurance Industry MHIVis:寿险保单持有人心理疾病的可视化分析

2020 7th International Conference on Behavioural and Social Computing (BESC) Pub Date : 2020-11-05 DOI: 10.1109/BESC51023.2020.9348301

Md. Rafiqul Islam, Shaowu Liu, Imran Razzak, M. A. Kabir, Xianzhi Wang, Peter Tilocca, Guandong Xu

引用次数: 9

Cooperative Norms and the Growth of Threat: Differences Across Tight and Loose Cultures 合作规范与威胁的增长:严格文化与宽松文化的差异

2020 7th International Conference on Behavioural and Social Computing (BESC) Pub Date : 2020-11-05 DOI: 10.1109/BESC51023.2020.9348297

Xinyue Pan, Dana S. Nau, M. Gelfand

引用次数: 2

Are They Likely to Complain on Phish or Spam? A Prediction Model 他们可能会抱怨网络钓鱼或垃圾邮件吗?预测模型

2020 7th International Conference on Behavioural and Social Computing (BESC) Pub Date : 2020-11-05 DOI: 10.1109/BESC51023.2020.9348318

S. Al-Hussaini, Dena Al-Thani, Y. Yang

{"title":"Are They Likely to Complain on Phish or Spam? A Prediction Model","authors":"S. Al-Hussaini, Dena Al-Thani, Y. Yang","doi":"10.1109/BESC51023.2020.9348318","DOIUrl":"https://doi.org/10.1109/BESC51023.2020.9348318","url":null,"abstract":"Customers are the core of businesses. Specifically, telecommunication companies, customer satisfaction is considered to be a commercial necessity and therefore a priority. High rates of customer satisfaction increase both retention and attraction rates. As a result, telecommunication companies are always seeking new means to achieve these objectives. A large volume of calls is received in a typical call center from customers complaining about phishing or spam attacks daily. It is difficult to identify the purpose of the call manually. In this work, we expand on previous efforts to focus more on impacted phone spam or phish consumers. The study focuses on both mediums of communication, phone calls and messages. A historical sample of customers' complaints dataset was used, and several machine learning classification algorithms were applied to analyze the calls. These are Logistic Regression, XGBoost, Gradient Boosting, Random Forest, CatBoost, KNN, and SVM. The predictive model can identify whether an individual is likely to complain about a spam or phish attack. The performance of the baseline classifier achieves an accuracy of 63.4 % that is based on CatBoost. Moreover, the model identifies consumers' demographics. The findings show that people of age 45 are more likely to complain and that males are less likely to complain.","PeriodicalId":224502,"journal":{"name":"2020 7th International Conference on Behavioural and Social Computing (BESC)","volume":"1 1","pages":"0"},"PeriodicalIF":0.0,"publicationDate":"2020-11-05","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"127022566","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: 0

A Lightweight Network for Fast Semantic Segmentation 一种快速语义分割的轻量级网络

2020 7th International Conference on Behavioural and Social Computing (BESC) Pub Date : 2020-11-05 DOI: 10.1109/BESC51023.2020.9348326

Ruiqi Luo, Yuanzhouhan Cao, Yi Jin, Yidong Li

引用次数: 0

An evolutionary algorithm for reducing fear of crime 一种减少对犯罪恐惧的进化算法

2020 7th International Conference on Behavioural and Social Computing (BESC) Pub Date : 2020-11-05 DOI: 10.1109/BESC51023.2020.9348330

Cristian Pulido, A. Reyes, J. Rudas, Jorge Victorino, Darwin Martínez, L. A. Narváez, Francisco Gómez

引用次数: 0

Eliciting Requirements for a Student-focussed Capture The Flag 引出以学生为中心的捕获旗帜的要求

2020 7th International Conference on Behavioural and Social Computing (BESC) Pub Date : 2020-11-05 DOI: 10.1109/BESC51023.2020.9348329

David Szedlak, Andrew M'manga

引用次数: 1

Knowledge Interaction Enhanced Knowledge Tracing for Learner Performance Prediction 知识交互增强的知识追踪用于学习者绩效预测

2020 7th International Conference on Behavioural and Social Computing (BESC) Pub Date : 2020-11-05 DOI: 10.1109/BESC51023.2020.9348285

Wenbin Gan, Yuan Sun, Yi Sun

{"title":"Knowledge Interaction Enhanced Knowledge Tracing for Learner Performance Prediction","authors":"Wenbin Gan, Yuan Sun, Yi Sun","doi":"10.1109/BESC51023.2020.9348285","DOIUrl":"https://doi.org/10.1109/BESC51023.2020.9348285","url":null,"abstract":"One of the fundamental tasks when providing personalized tutoring services to learners in online learning systems is to predict learner performance on future exercises. To achieve this goal, it is necessary to estimate and trace the knowledge proficiency (KP) of learners by modeling their learning performance. The existing models either fail to capture the long-term dependencies in the exercising sequence to model the influence of a previous exercise to the current one or find it difficult to explain the results. To solve these issues, we propose herein a novel model, called the knowledge interaction-enhanced knowledge tracing (KIKT), to estimate and trace the evolution of learners' KP. We first propose a framework by unifying the strength of the memory network to enhance the representation of the knowledge state and the interpretability of the Item Response Theory to explain learner performance. In this framework, we trace each learner's KP on each knowledge concept overtime, and further infer their proficiencies and the item characteristics using two kinds of neural networks. Moreover, we incorporate the knowledge interaction and the cognitive difficulty into our model to further exploit the long-term dependencies and the adaptive item difficulty in the exercising sequences. Extensive experiments conducted on five real-world datasets demonstrate the superiority of our model.","PeriodicalId":224502,"journal":{"name":"2020 7th International Conference on Behavioural and Social Computing (BESC)","volume":"75 1","pages":"0"},"PeriodicalIF":0.0,"publicationDate":"2020-11-05","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"127724330","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: 6

Human Capital Structure and High-Quality Development: An Empirical Study 人力资本结构与高质量发展的实证研究

2020 7th International Conference on Behavioural and Social Computing (BESC) Pub Date : 2020-11-05 DOI: 10.1109/BESC51023.2020.9348289

Wenwen Qin, Jun Xue, M. Wei

引用次数: 0

A Joint Model of Entity Recognition and Predicate Mapping for Chinese Knowledge Base Question Answering 面向中文知识库问答的实体识别与谓词映射联合模型

2020 7th International Conference on Behavioural and Social Computing (BESC) Pub Date : 2020-11-05 DOI: 10.1109/BESC51023.2020.9348292

Hongjing Li, Lin Li

{"title":"A Joint Model of Entity Recognition and Predicate Mapping for Chinese Knowledge Base Question Answering","authors":"Hongjing Li, Lin Li","doi":"10.1109/BESC51023.2020.9348292","DOIUrl":"https://doi.org/10.1109/BESC51023.2020.9348292","url":null,"abstract":"Knowledge base question answering(KBQA) is the key technology of natural language processing. How to understand the semantic information of the natural language problem and capture the semantic relationship between the problem and the structured triples are the problems that KBQA needs to solve. The boundary of subject entities in Chinese questions is not as clear as English, which increases the difficulty of entity recognition. Besides, the variable Chinese grammar makes predicate mapping more difficult for semantic analysis. Existing KBQA is usually implemented using a pipeline model, which has two disadvantages: (1) Errors caused by entity recognition will be propagated to predicate mapping. (2) Neither entity recognition nor predicate mapping can benefit from the information available to each other. So we propose a BERT-based KBQA to joint entity recognition and predicate mapping tasks that use their dependencies to improve model performance. BERT can solve the semantic ambiguity of the Chinese Q&A databases and improve the accuracy of Chinese Knowledge Base Question Answering(CKBQA). The model achieved an F1 score of 92.04% on the NLPCC 2016 KBQA dataset.","PeriodicalId":224502,"journal":{"name":"2020 7th International Conference on Behavioural and Social Computing (BESC)","volume":"602 1","pages":"0"},"PeriodicalIF":0.0,"publicationDate":"2020-11-05","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"131241527","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: 1

IT Investment Governance and Corporate Governance: Perspective and Approach IT投资治理与公司治理:观点与方法

2020 7th International Conference on Behavioural and Social Computing (BESC) Pub Date : 2020-11-05 DOI: 10.1109/BESC51023.2020.9348312

Abhishek Mahalle, J. Yong, Xiaohui Tao

{"title":"IT Investment Governance and Corporate Governance: Perspective and Approach","authors":"Abhishek Mahalle, J. Yong, Xiaohui Tao","doi":"10.1109/BESC51023.2020.9348312","DOIUrl":"https://doi.org/10.1109/BESC51023.2020.9348312","url":null,"abstract":"Corporate Governance, Business plan and Strategy and it's alignment with IT investments has been a subject of discussion as early as 1990s. With productivity paradox and net present value (and other financial methods) of IT investments researched over a period of time, this paper is to put perspective for IT investment in present economic scenario with latest technologies and in digital world. With cloud computing infrastructure requiring all other IT governance principles and processes to be followed, IT investment demands investment more than only in hardware and software development, maintenance and support. IT investment and it's relation to corporate strategy, business risk management, information economics, new business enabler, productivity tool, control systems to deliver shareholder value and constantly create business value has emerged to new domain. Innovation, it's relation to technology, technological innovations and their relation to competitive advantage for an organization has created new areas that demand investment. With competition in business environment and integrated global economy, regulators demand more compliant business processes delivered through modern technological infrastructure. Having investigated the financial, non-financial, economic, tangible and non-tangible benefits of IT investment, this paper provides the new perspective to assess IT investments and make IT investment decision. This papers provides new perspectives and approaches for IT investment portfolio management.","PeriodicalId":224502,"journal":{"name":"2020 7th International Conference on Behavioural and Social Computing (BESC)","volume":"32 1","pages":"0"},"PeriodicalIF":0.0,"publicationDate":"2020-11-05","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"129612814","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: 1