International Conference on Crowd Science and Engineering最新文献_第5页

Optimal Crowds Contest Model for Crowdsourcing 众包的最优人群竞赛模型

International Conference on Crowd Science and Engineering Pub Date : 2017-07-06 DOI: 10.1145/3126973.3126982

Song Xu, Lei Liu, Li-zhen Cui, Yongqing Zheng

引用次数: 4

Deep Model for Dropout Prediction in MOOCs 基于深度模型的mooc辍学预测

International Conference on Crowd Science and Engineering Pub Date : 2017-07-06 DOI: 10.1145/3126973.3126990

Wei Wang, Han Yu, C. Miao

引用次数: 112

Population Distribution Projection by Modeling Geo Homophily in Online Social Networks 基于地理同质性模型的在线社交网络人口分布预测

International Conference on Crowd Science and Engineering Pub Date : 2017-07-06 DOI: 10.1145/3126973.3127000

Yuanxing Zhang, Zhuqi Li, Kaigui Bian, Yichong Bai, Zhi Yang, Xiaoming Li

{"title":"Population Distribution Projection by Modeling Geo Homophily in Online Social Networks","authors":"Yuanxing Zhang, Zhuqi Li, Kaigui Bian, Yichong Bai, Zhi Yang, Xiaoming Li","doi":"10.1145/3126973.3127000","DOIUrl":"https://doi.org/10.1145/3126973.3127000","url":null,"abstract":"Today, many applications depend on the projection on the population distribution in geographical regions, such as launching marketing campaigns and enhancing the public safety in certain densely-populated areas. Demographic and sociological researches have provided various ways of collecting people's trajectory data through offline means. However, collecting offline data consumes a lot of resources, and the data availability is usually limited. Fortunately, the wide spread of online social network (OSN) applications over mobile devices reflect many geographical information, where we could devise a light weight approach of conducting the study on the projection of the population distribution using the online data. In this paper, we propose a geo-homophily model in OSNs to help project the population distribution in a given division of geographical regions. We establish a three-layer theoretic framework: It first describes the relationship between the online message diffusion among friends in the OSN and the offline population distribution over a given division of regions via a Dirichlet process, and then projects the floating population across the regions. Evaluations over large-scale OSN datasets show that the proposed prediction models can characterize the process of the formation of the population distribution and the changes of the floating population over time with a high prediction accuracy.","PeriodicalId":370356,"journal":{"name":"International Conference on Crowd Science and Engineering","volume":"48 1","pages":"0"},"PeriodicalIF":0.0,"publicationDate":"2017-07-06","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"121100257","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

Empirical Study on Assessment Algorithms with Confidence in Crowdsourcing 众包中有信心评估算法的实证研究

International Conference on Crowd Science and Engineering Pub Date : 2017-07-06 DOI: 10.1145/3126973.3126994

Yiming Cao, Lei Liu, Li-zhen Cui, Qingzhong Li

引用次数: 2

A MCIN-based Architecture of Smart Agriculture 基于mcin的智慧农业体系结构

International Conference on Crowd Science and Engineering Pub Date : 2017-07-06 DOI: 10.1145/3126973.3126999

Xiang Gu, Y. Chai, Yi Liu, Jianping Shen, Yadong Huang, Yixuan Nan

引用次数: 9

Towards Age-friendly E-commerce Through Crowd-Improved Speech Recognition, Multimodal Search, and Personalized Speech Feedback 通过群体改进语音识别、多模式搜索和个性化语音反馈实现老年人友好型电子商务

International Conference on Crowd Science and Engineering Pub Date : 2017-07-06 DOI: 10.1145/3126973.3129306

L. Meng, Nguyen Quy Hy, Xiaohai Tian, Zhiqi Shen, Chng Eng Siong, F. Guan, C. Miao, Cyril Leung

{"title":"Towards Age-friendly E-commerce Through Crowd-Improved Speech Recognition, Multimodal Search, and Personalized Speech Feedback","authors":"L. Meng, Nguyen Quy Hy, Xiaohai Tian, Zhiqi Shen, Chng Eng Siong, F. Guan, C. Miao, Cyril Leung","doi":"10.1145/3126973.3129306","DOIUrl":"https://doi.org/10.1145/3126973.3129306","url":null,"abstract":"This paper presents an age-friendly system for improving the elderly's online shopping experience. Different from most related studies focusing on website design and content organization, we propose to integrate three assistive techniques to facilitate the elderly's browsing of products in E-commerce platforms, including the crowd-improved speech recognition, the multimodal search, and the personalized speech feedback. The first two techniques, namely, the crowd-improved speech recognition and the multimodal search, work together to allow the elderly search for desired products flexibly using either speech, an image, text, or any combination of them whichever are convenient for the elderly. The personalized speech feedback provides a speech summary of search result in a personalized voice. That is, the elderly are allowed to choose or even create their desired voices, and also can customize the voices in terms of pitch, speaking speed, and loudness. As a whole, the proposed system is expected to help and engage the elderly's E-commerce adoption. Testing on real-world E-commerce product datasets demonstrated the usability of the proposed system.","PeriodicalId":370356,"journal":{"name":"International Conference on Crowd Science and Engineering","volume":"63 1","pages":"0"},"PeriodicalIF":0.0,"publicationDate":"2017-07-06","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"124752625","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: 9

A Risky Driving Behavior Scoring Model for the Personalized Automobile Insurance Pricing 个性化汽车保险定价中的危险驾驶行为评分模型

International Conference on Crowd Science and Engineering Pub Date : 2017-07-06 DOI: 10.1145/3126973.3126978

Zhishuo Liu, Qianhui Shen, Han Li, Jingmiao Ma

{"title":"A Risky Driving Behavior Scoring Model for the Personalized Automobile Insurance Pricing","authors":"Zhishuo Liu, Qianhui Shen, Han Li, Jingmiao Ma","doi":"10.1145/3126973.3126978","DOIUrl":"https://doi.org/10.1145/3126973.3126978","url":null,"abstract":"Telematics1 techniques enable insurers to capture the driving behavior of policyholders and correspondingly offer the personalized vehicle insurance rate, namely the usage-based insurance (UBI). A risky driving behavior scoring model for the personalized automobile insurance pricing was proposed based on telematics data. Firstly, three typical UBI pricing modes were analyzed. Drive behavior rate factors (DBRF) pricing mode was proposed based on mileage rate factors (MRF), in which insurance rate for each vehicle can be determined by the evaluation of individual driving behavior using OBD data. Then, on the basis of the analysis of influencing factors of safe driving, a driving behavior score model was established for DBRF by the improved EW-AHP (Entropy Weight- Analytic Hierarchy Process) Method. Finally, driving behavior scores of 100 drivers were computed by using the data collected from a 6-month field experiment. The results of three statistics analysis showed that the driving behavior score model could effectively reflect the risk level of driver's safe driving and provide a basis for the individual discount or surcharge that insurers offer to their policyholders.","PeriodicalId":370356,"journal":{"name":"International Conference on Crowd Science and Engineering","volume":"13 1","pages":"0"},"PeriodicalIF":0.0,"publicationDate":"2017-07-06","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"130862254","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: 7

A Reputation Model for Aggregating Ratings based on Beta Distribution Function 基于Beta分布函数的评级聚合信誉模型

International Conference on Crowd Science and Engineering Pub Date : 2017-07-06 DOI: 10.1145/3126973.3126992

Y. Liu, Usman Shittu Chitawa, G. Guo, Xingwei Wang, Zhenhua Tan, Shuang Wang

{"title":"A Reputation Model for Aggregating Ratings based on Beta Distribution Function","authors":"Y. Liu, Usman Shittu Chitawa, G. Guo, Xingwei Wang, Zhenhua Tan, Shuang Wang","doi":"10.1145/3126973.3126992","DOIUrl":"https://doi.org/10.1145/3126973.3126992","url":null,"abstract":"With the speed growth of financial technology (Fintech), modern electronic marketing has typically deployed the use of the World Wide Web. This has come with great challenges especially in decision making and in engaging the pre-tail for launching new products and services in an open environment susceptible to high risks and threats. A prodigious need to build a sellers reputation and trust between the seller and the buyer so as to diminish such risks and threats in online trading birthed the idea of reputation systems. The emergence of reputation systems has attracted a lot of researchers to propose rating aggregation methods such as simple mean and normal distribution based method. However, the existing methods cannot accurately produce reputation score in some cases. Hence, this paper proposes a new model aiming to producing even more accurate and effective reputation score. Our model uses the standard beta-distribution considering the received rating distribution, so as to generate the weights of each ratings and then derive the level weights of ratings. The final reputation score is the level weighted aggregation of the rating levels. The proposed model is innovative in the aspect that the ratings are not directly aggregated to the reputation score, but are treated as the samples in evaluating each respective rating levels. Through case studies, the model is demonstrated to achieve desired accuracy and effectiveness, and even performs better than the existing models.","PeriodicalId":370356,"journal":{"name":"International Conference on Crowd Science and Engineering","volume":"137 1","pages":"0"},"PeriodicalIF":0.0,"publicationDate":"2017-07-06","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"132749408","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: 8

A sleep stage classification algorithm based on radial basis function networks 基于径向基函数网络的睡眠阶段分类算法

International Conference on Crowd Science and Engineering Pub Date : 2017-07-06 DOI: 10.1145/3126973.3126976

Zhihong Cui, Xiangwei Zheng

引用次数: 2

Compressing Trajectory for Trajectory Indexing 为轨迹索引压缩轨迹

International Conference on Crowd Science and Engineering Pub Date : 2017-07-06 DOI: 10.1145/3126973.3126979

Kaiyu Feng, Zhiqi Shen

引用次数: 0