2018 IEEE 15th International Conference on e-Business Engineering (ICEBE)最新文献_第6页

Personalized Intelligent Push Method of Design Tasks for Designers in the Hackerspace Hackerspace中设计师设计任务的个性化智能推送方法

2018 IEEE 15th International Conference on e-Business Engineering (ICEBE) Pub Date : 2018-10-01 DOI: 10.1109/ICEBE.2018.00040

C. Cheng, Shuyou Zhang

引用次数: 1

Linked Open Data-Driven Contrastive Cognitive Subgraph Searching for Understanding Concepts in e-Learning 链接开放数据驱动的对比认知子图搜索在电子学习中的理解概念

2018 IEEE 15th International Conference on e-Business Engineering (ICEBE) Pub Date : 2018-10-01 DOI: 10.1109/ICEBE.2018.00050

Mengge Liu, Feng Tian, Yundong Yao, Y. Ni, Yan Chen, Haiping Zhu, Q. Zheng

{"title":"Linked Open Data-Driven Contrastive Cognitive Subgraph Searching for Understanding Concepts in e-Learning","authors":"Mengge Liu, Feng Tian, Yundong Yao, Y. Ni, Yan Chen, Haiping Zhu, Q. Zheng","doi":"10.1109/ICEBE.2018.00050","DOIUrl":"https://doi.org/10.1109/ICEBE.2018.00050","url":null,"abstract":"Along with rise of e-learning, searching services as an important part of e-learning system has attracted more and more e-learners and researchers. According to theory of cognitive development, when e-learners are having problems to understand a concept during online learning, they prefer to search related information to form new cognitive structures or strengthen existing cognitive structures in order to improve learning efficiency. Although the existing search engines are extremely mature, they play a less role in cognitive structures for e-learners. Depending on the theory of constructivism, an effective mean to improve cognitive efficiency is to enhance the improvement and development of individual cognitive structure. Therefore, relying on thinking map, we develop a Linked Open Data-driven contrastive cognitive subgraph searching system for understanding concepts. Besides, during constructing contrastive cognitive subgraphs, we propose a method of calculating similarity between two keywords, whose accuracy and stability have been effectively improved compared with the other algorithm on LOD.","PeriodicalId":221376,"journal":{"name":"2018 IEEE 15th International Conference on e-Business Engineering (ICEBE)","volume":"82 1","pages":"0"},"PeriodicalIF":0.0,"publicationDate":"2018-10-01","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"131876046","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 Case Study of Service-Centric IoT Model for Rural Sewage Disposal 以服务为中心的农村污水处理物联网模型研究

2018 IEEE 15th International Conference on e-Business Engineering (ICEBE) Pub Date : 2018-10-01 DOI: 10.1109/ICEBE.2018.00029

Zheng Liu, Beibei Yu, Zhibo Chen, Jiqin Peng, Qiang Feng, Qing Liu, Cheng Xie

{"title":"A Case Study of Service-Centric IoT Model for Rural Sewage Disposal","authors":"Zheng Liu, Beibei Yu, Zhibo Chen, Jiqin Peng, Qiang Feng, Qing Liu, Cheng Xie","doi":"10.1109/ICEBE.2018.00029","DOIUrl":"https://doi.org/10.1109/ICEBE.2018.00029","url":null,"abstract":"The Internet of Things (IoT) refers to an emerging paradigm, to seamlessly and ubiquitously integrate a large number of smart things with intra/inter links to the physical and cyber worlds. The sensor enabled communication technologies are connecting billions of things, by efficiently utilizing their locations in the real world. However, how to use a reasonable architecture to build IoT services via heterogeneous and distributed smart things and sensors is an important and challenging issue, especially in rural areas where power and network resources are relatively scarce. In this work, to catch the challenge, we propose an Integrated IoT service model for distributed sensors. By modeling sensors into information resources, a RESTful service model is applied to each sensor. By using IoT based service adapter, information resources are integrated into service center which is feasible be accessed by electrical power and wireless network. A case study of rural sewage disposal is conducted based on the proposed service model. Also, a developed prototype system of rural sewage disposal shows the feasibility and effectiveness of the proposed model.","PeriodicalId":221376,"journal":{"name":"2018 IEEE 15th International Conference on e-Business Engineering (ICEBE)","volume":"71 1","pages":"0"},"PeriodicalIF":0.0,"publicationDate":"2018-10-01","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"133467657","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

Mining Emotions of the Public from Social Media for Enhancing Corporate Credit Rating 挖掘社交媒体公众情绪提升企业信用评级

2018 IEEE 15th International Conference on e-Business Engineering (ICEBE) Pub Date : 2018-10-01 DOI: 10.1109/ICEBE.2018.00015

Hui Yuan, Raymond Y. K. Lau, Michael C. S. Wong, Chunping Li

{"title":"Mining Emotions of the Public from Social Media for Enhancing Corporate Credit Rating","authors":"Hui Yuan, Raymond Y. K. Lau, Michael C. S. Wong, Chunping Li","doi":"10.1109/ICEBE.2018.00015","DOIUrl":"https://doi.org/10.1109/ICEBE.2018.00015","url":null,"abstract":"The proliferation of online social media has been changing the ways how individuals interact with corporations. Previous studies have examined how to extract investors' sentiments captured on social media to enhance stock prediction. However, little work was done to leverage public's emotions captured on social media to predict corporate credit risks. Our research fills the current research gap by developing a new computational method to extract public's emotions embedded in social postings to supplement common financial indicators (e.g., return-on-assets) for predicting corporate credit ratings. Grounded in Plutchik's Wheel of Emotions, the proposed computational framework can automatically extract the distribution of eight basic emotions from textual postings on online social media. In particular, one main contribution of our work is the development of the new emotion latent dirichlet allocation (ELDA) model for textual emotion analysis. In addition, we develop an ensemble learning model with random forest (RF) as the basis classifier to improve the performance of corporate credit rating. Based on the real-world data crawled from Twitter, our experimental results confirm that the proposed ELDA model can effectively and efficiently extract public's emotions from social postings to enhance the prediction of corporate credit ratings. To our best knowledge, this is the first successful research of developing a new computational model of extracting public's emotions from social postings to enhance corporate credit risk prediction.","PeriodicalId":221376,"journal":{"name":"2018 IEEE 15th International Conference on e-Business Engineering (ICEBE)","volume":"29 1","pages":"0"},"PeriodicalIF":0.0,"publicationDate":"2018-10-01","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"126517198","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

Title Page i 第1页

2018 IEEE 15th International Conference on e-Business Engineering (ICEBE) Pub Date : 2018-10-01 DOI: 10.1109/icebe.2018.00001

引用次数: 0