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2018 14th International Conference on Semantics, Knowledge and Grids (SKG)最新文献

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A Simplified Deep Residual Network for Citywide Crowd Flows Prediction 基于简化深度残差网络的城市人群流量预测
2018 14th International Conference on Semantics, Knowledge and Grids (SKG) Pub Date : 2018-09-01 DOI: 10.1109/SKG.2018.00016
Xiaoyang Hu, Genan Dai, Youming Ge, Zhiqing Ning, Yubao Liu
{"title":"A Simplified Deep Residual Network for Citywide Crowd Flows Prediction","authors":"Xiaoyang Hu, Genan Dai, Youming Ge, Zhiqing Ning, Yubao Liu","doi":"10.1109/SKG.2018.00016","DOIUrl":"https://doi.org/10.1109/SKG.2018.00016","url":null,"abstract":"Crowd flows prediction is an important problem of urban computing. The existing best-known method adopts deep residual networks to model spatio-temporal properties and often achieves good prediction performance. However, since three separated network structures are used to model the properties, the time cost is often expensive for the best-known method. In this paper, we propose an improved method to reduce the running time of the best-known method by simplifying its architecture. Compared with the best-known method, the training time and predicting time of our method can be reduced dramatically. Moreover, the improved method can achieve similar prediction performance with the best-known method. Extensive experiments on the real-world datasets were conducted to show the efficiency of our proposed method.","PeriodicalId":265760,"journal":{"name":"2018 14th International Conference on Semantics, Knowledge and Grids (SKG)","volume":"1 1","pages":"0"},"PeriodicalIF":0.0,"publicationDate":"2018-09-01","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"129825245","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: 4
Crowdsourcing with Fewer Workers 用更少的工人众包
2018 14th International Conference on Semantics, Knowledge and Grids (SKG) Pub Date : 2018-09-01 DOI: 10.1109/SKG.2018.00023
Xiaoyu Huang, Zhengzheng Xian, Qingsong Zeng
{"title":"Crowdsourcing with Fewer Workers","authors":"Xiaoyu Huang, Zhengzheng Xian, Qingsong Zeng","doi":"10.1109/SKG.2018.00023","DOIUrl":"https://doi.org/10.1109/SKG.2018.00023","url":null,"abstract":"The crowdsourcing mechanism, as an effective and economic alternative in data science study, has attracted substantial research interests in recent years. However, despite of numerous successful crowdsourcing applications, many crowdsourcers still suffer from the high cost issue. This is mainly due to the fact that most of the crowd workers are usually not professional experts, and thus, in order to ensure the quality of crowdsourcing, extra investment is introduced by hiring many crowd workers to work on every task multiple times to inhabit the noisy submissions. In this article, we propose an approach that can mitigate the crowdsourcer's investment by using less human efforts while at the same time still has provable guarantees for the refined results. Experimental results on two real-world datasets are inspiring and consistent with the theoretical analysis.","PeriodicalId":265760,"journal":{"name":"2018 14th International Conference on Semantics, Knowledge and Grids (SKG)","volume":"1 1","pages":"0"},"PeriodicalIF":0.0,"publicationDate":"2018-09-01","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"130761209","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
Bonus Points Alliance Based on the Block Chain 基于区块链的积分联盟
2018 14th International Conference on Semantics, Knowledge and Grids (SKG) Pub Date : 2018-09-01 DOI: 10.1109/SKG.2018.00045
Chang Chen, X. Sun, Gehao Lu, Hongwei Kang, Yong Shen
{"title":"Bonus Points Alliance Based on the Block Chain","authors":"Chang Chen, X. Sun, Gehao Lu, Hongwei Kang, Yong Shen","doi":"10.1109/SKG.2018.00045","DOIUrl":"https://doi.org/10.1109/SKG.2018.00045","url":null,"abstract":"In this paper, a new Bonus Points Alliance is designed based on the key technology of Block chain. We make use of the technical features of decentralization, trust-consensus, distributed network, collective maintenance and so on and research on Bonus Points Alliance business model based on block chain. We take advantage of the key technologies such as consensus mechanism and smart contract in block chain and take the “alliance blockchain” as a form of organization to design a full technical solution which solves the shortcomings of traditional alliance, such as a high cost of system development, difficulty of bonus points exchange, and difficulty of bonus points circulate.","PeriodicalId":265760,"journal":{"name":"2018 14th International Conference on Semantics, Knowledge and Grids (SKG)","volume":"27 1","pages":"0"},"PeriodicalIF":0.0,"publicationDate":"2018-09-01","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"124386492","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: 3
Social Network Influence Propagation Model Based on Emotion Analysis 基于情感分析的社会网络影响传播模型
2018 14th International Conference on Semantics, Knowledge and Grids (SKG) Pub Date : 2018-09-01 DOI: 10.1109/SKG.2018.00022
Xueyan Liu, Gui Sun, Hongtao Liu, Jie Jian
{"title":"Social Network Influence Propagation Model Based on Emotion Analysis","authors":"Xueyan Liu, Gui Sun, Hongtao Liu, Jie Jian","doi":"10.1109/SKG.2018.00022","DOIUrl":"https://doi.org/10.1109/SKG.2018.00022","url":null,"abstract":"Online social networking provides an open platform for public to express their views on an event or product. Obviously the user's emotion would affect the propagation of the event influence. To reflect the propagation of influence in social networks more accurately, this paper firstly improved the Independent Cascade Model, adding the emotion factor to the formula of the propagation probability. Secondly we used the improved model to predict the spread of influence. Thirdly, we carried the simulation experiment to analyse its propagation effect on Sina Micro-blog dataset. The experimental results show that the improved influence propagation model has certain improvement in the propagation effect than that before the improvement.","PeriodicalId":265760,"journal":{"name":"2018 14th International Conference on Semantics, Knowledge and Grids (SKG)","volume":"10 1","pages":"0"},"PeriodicalIF":0.0,"publicationDate":"2018-09-01","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"121792358","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
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