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2019 20th IEEE International Conference on Mobile Data Management (MDM)最新文献

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KOLQ in a Road Network 道路网络中的KOLQ
2019 20th IEEE International Conference on Mobile Data Management (MDM) Pub Date : 2019-06-01 DOI: 10.1109/MDM.2019.00-71
Zitong Chen, Yubao Liu, A. Fu, R. C. Wong, Genan Dai
{"title":"KOLQ in a Road Network","authors":"Zitong Chen, Yubao Liu, A. Fu, R. C. Wong, Genan Dai","doi":"10.1109/MDM.2019.00-71","DOIUrl":"https://doi.org/10.1109/MDM.2019.00-71","url":null,"abstract":"Optimal location querying (OLQ) in road networks is important for various applications. Existing work assumes no labels for servers and that a client only visits the nearest server. These assumptions are not realistic and it renders the existing work not useful in many cases. In this paper, we introduce the KOLQ problem which considers the k nearest servers of clients and labeled servers. We also proposed algorithms for the problem. Extensive experiments on the real road networks illustrate the efficiency of our proposed solutions.","PeriodicalId":241426,"journal":{"name":"2019 20th IEEE International Conference on Mobile Data Management (MDM)","volume":"22 1","pages":"0"},"PeriodicalIF":0.0,"publicationDate":"2019-06-01","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"123667952","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
Message from the Mobile Data & AI Special Track Chairs 来自移动数据和人工智能特殊轨道椅的信息
2019 20th IEEE International Conference on Mobile Data Management (MDM) Pub Date : 2019-06-01 DOI: 10.1109/mdm.2019.00-96
{"title":"Message from the Mobile Data & AI Special Track Chairs","authors":"","doi":"10.1109/mdm.2019.00-96","DOIUrl":"https://doi.org/10.1109/mdm.2019.00-96","url":null,"abstract":"","PeriodicalId":241426,"journal":{"name":"2019 20th IEEE International Conference on Mobile Data Management (MDM)","volume":"96 1","pages":"0"},"PeriodicalIF":0.0,"publicationDate":"2019-06-01","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"124903385","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
Privacy-Protected Blockchain System 隐私保护区块链系统
2019 20th IEEE International Conference on Mobile Data Management (MDM) Pub Date : 2019-06-01 DOI: 10.1109/MDM.2019.000-2
Ping Zhong, Qikai Zhong, Haibo Mi, Shigeng Zhang, Yang Xiang
{"title":"Privacy-Protected Blockchain System","authors":"Ping Zhong, Qikai Zhong, Haibo Mi, Shigeng Zhang, Yang Xiang","doi":"10.1109/MDM.2019.000-2","DOIUrl":"https://doi.org/10.1109/MDM.2019.000-2","url":null,"abstract":"The blockchain uses a decentralized consensus mechanism to maintain the books in an immutable way, which ensures the blockchain smart contract system highly secure. In existing blockchain systems, all user information is disclosed in the blockchain. However, currently users begin to pay more and more attention to personal privacy, therefore the future blockchain smart contract system needs not only to keep immutability but also to protect user privacy. To achieve this goal, in this paper we propose a privacy-encrypted blockchain system, where all data is encrypted within a controllable period of time. Although the data is visible from a historical perspective, our design can effectively protect user privacy and against deceivers, making the system more secure and healthy.","PeriodicalId":241426,"journal":{"name":"2019 20th IEEE International Conference on Mobile Data Management (MDM)","volume":"72 1","pages":"0"},"PeriodicalIF":0.0,"publicationDate":"2019-06-01","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"129022873","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: 10
CLEAN: Frequent Pattern-Based Trajectory Spatial-Temporal Compression on Road Networks 基于频繁模式的道路网络轨迹时空压缩
2019 20th IEEE International Conference on Mobile Data Management (MDM) Pub Date : 2019-06-01 DOI: 10.1109/MDM.2019.00127
Peng Zhao, Qinpei Zhao, Chenxi Zhang, Gong Su, Qi Zhang, Weixiong Rao
{"title":"CLEAN: Frequent Pattern-Based Trajectory Spatial-Temporal Compression on Road Networks","authors":"Peng Zhao, Qinpei Zhao, Chenxi Zhang, Gong Su, Qi Zhang, Weixiong Rao","doi":"10.1109/MDM.2019.00127","DOIUrl":"https://doi.org/10.1109/MDM.2019.00127","url":null,"abstract":"The volume of trajectory data has become tremendously large in recent years. How to efficiently maintain and compute such trajectory data becomes a challenging task. In this paper, we propose a trajectory spatial and temporal compression framework, namely CLEAN. The key of spatial compression is to mine meaningful trajectory frequent patterns on road networks. By treating the mined patterns as dictionary items, we have the chance to encode a long trajectory by shorter paths, thus leading to smaller space cost. Meanwhile, we design an error-bounded temporal compression on top of the identified spatial patterns for much low space cost. Extensive experiments on real trajectory datasets validate that CLEAN significantly outperforms existing state-of-art approaches in terms of both space saving and runtime of trajectory compression.","PeriodicalId":241426,"journal":{"name":"2019 20th IEEE International Conference on Mobile Data Management (MDM)","volume":"28 5","pages":"0"},"PeriodicalIF":0.0,"publicationDate":"2019-06-01","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"132610976","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
A Safe, Efficient and Integrated Indoor Robotic Fleet for Logistic Applications in Healthcare and Commercial Spaces: The ENDORSE Concept 一个安全、高效和集成的室内机器人车队，用于医疗和商业空间的物流应用:背书概念
2019 20th IEEE International Conference on Mobile Data Management (MDM) Pub Date : 2019-06-01 DOI: 10.1109/MDM.2019.000-8
N. Ramdani, A. Panayides, Michalis Karamousadakis, M. Mellado, Rafael Lopez, C. Christophorou, Mohamed Rebiai, Myriam Blouin, E. Vellidou, D. Koutsouris
{"title":"A Safe, Efficient and Integrated Indoor Robotic Fleet for Logistic Applications in Healthcare and Commercial Spaces: The ENDORSE Concept","authors":"N. Ramdani, A. Panayides, Michalis Karamousadakis, M. Mellado, Rafael Lopez, C. Christophorou, Mohamed Rebiai, Myriam Blouin, E. Vellidou, D. Koutsouris","doi":"10.1109/MDM.2019.000-8","DOIUrl":"https://doi.org/10.1109/MDM.2019.000-8","url":null,"abstract":"Hospitals are rightfully considered a field of indoor logistic robotics of high commercial potential. However, today, only a handful of mobile robotic solutions for hospital logistics exist that have failed to trigger widespread acceptance by the market. This is because existing systems require costly infrastructure installation, they do not easily integrate to corporate IT solutions, are not adequately shielded from cybersecurity threats, and as a result, they do not fully automate procedures and traceability of the items they carry. Moreover, existing systems are limited on scope, focusing only on delivery services, and hence do not provide any other type of support to the medical and nursing staff. ENDORSE system will address the aforementioned technical challenges and functional limitations by pursuing four innovation pillars: (i) infrastructure-less multi-robot indoor navigation; (ii) advanced Human-Robot Interaction (HRI) for resolving deadlocks and achieving efficient sharing of space resources in crowded environments; (iii) deployment of the ENDORSE software as a cloud-based service facilitating its integration with corporate software solutions, complying with GDPR data security requirements; (iv) reconfigurable and modular hardware architectures so that diverse modules can be easily swapped. ENDORSE functionality will be demonstrated via the integration of an e-diagnostic support module for vital signs monitoring on a fleet of mobile robots, facilitating connectivity to cloud-based Electronic Health Records (EHR), and validated in an operational hospital environment for realistic assessment.","PeriodicalId":241426,"journal":{"name":"2019 20th IEEE International Conference on Mobile Data Management (MDM)","volume":"25 1","pages":"0"},"PeriodicalIF":0.0,"publicationDate":"2019-06-01","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"124282289","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: 13
TrajSense: Trajectory Prediction from Sparse and Missing External Sensor Data TrajSense:基于稀疏和缺失外部传感器数据的轨迹预测
2019 20th IEEE International Conference on Mobile Data Management (MDM) Pub Date : 2019-06-01 DOI: 10.1109/MDM.2019.00-29
L. A. Cruz, K. Zeitouni, J. Macêdo, Igo Ramalho Brilhante
{"title":"TrajSense: Trajectory Prediction from Sparse and Missing External Sensor Data","authors":"L. A. Cruz, K. Zeitouni, J. Macêdo, Igo Ramalho Brilhante","doi":"10.1109/MDM.2019.00-29","DOIUrl":"https://doi.org/10.1109/MDM.2019.00-29","url":null,"abstract":"In this demonstration, we present a framework to predict the movement of moving objects under the circumstance where external sensors placed on the road-sides (e.g., traffic surveillance cameras) capture their trajectories. The reported positions in such trajectories are sparse due to the sparsity of the sensor distribution, and incomplete, since the sensors may fail to register the passage of objects. In our framework, we cope with the missing data coming from the external sensor trajectories, which improves the quality of predictions in terms of accuracy and closeness in the road network.","PeriodicalId":241426,"journal":{"name":"2019 20th IEEE International Conference on Mobile Data Management (MDM)","volume":"22 1","pages":"0"},"PeriodicalIF":0.0,"publicationDate":"2019-06-01","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"129778330","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 Semantic Sequential Correlation Based LSTM Model for Next POI Recommendation 基于语义顺序相关的LSTM下一个POI推荐模型
2019 20th IEEE International Conference on Mobile Data Management (MDM) Pub Date : 2019-06-01 DOI: 10.1109/MDM.2019.00-65
Guanhua Zhan, Jian Xu, Zhifeng Huang, Qiang Zhang, Ming Xu, Ning Zheng
{"title":"A Semantic Sequential Correlation Based LSTM Model for Next POI Recommendation","authors":"Guanhua Zhan, Jian Xu, Zhifeng Huang, Qiang Zhang, Ming Xu, Ning Zheng","doi":"10.1109/MDM.2019.00-65","DOIUrl":"https://doi.org/10.1109/MDM.2019.00-65","url":null,"abstract":"The widespread of location-based social networks has generated massive check-in sequences in chronological order. Forecasting check-in sequences is significant while challenging due to the check-ins' sparsity problem. Existing methods have followed closely to incorporate spatial and temporal context to alleviate the data sparsity problem, but neglect the semantic sequential correlation between check-ins. Howbeit, incorporating the semantic sequential correlation between check-ins for next POI recommendation encounters the challenges of semantic sequential correlation measurement and sequential behavior modeling. To measure the semantic sequential correlation, we apply a semantic sequential correlation calculation model based on a semantic correlational graph that incorporates the time intervals' influence to calculate the semantic sequential correlation. Then, we apply a novel Long Short-Term Memory (LSTM) framework equipped with two additional semantic gates that takes the additional semantic sequential correlation as the extra input to capture users' sequential behaviors and model their long short-term interest with the restrictions in the semantic level. Finally, we cluster users into different groups as an improvement of our model to achieve a more accurate recommendation. Our proposed model is evaluated on a real-world and large-scale dataset and the experimental results demonstrate that our method outperforms the state-of-the-art methods for next POI recommendation.","PeriodicalId":241426,"journal":{"name":"2019 20th IEEE International Conference on Mobile Data Management (MDM)","volume":"2 1","pages":"0"},"PeriodicalIF":0.0,"publicationDate":"2019-06-01","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"128847439","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
Message from the Demonstration Track Chairs 来自示范轨道椅的信息
2019 20th IEEE International Conference on Mobile Data Management (MDM) Pub Date : 2019-06-01 DOI: 10.1109/mdm.2019.00-94
Mohamed Elsayed, Baihua Zheng, K. Zheng
{"title":"Message from the Demonstration Track Chairs","authors":"Mohamed Elsayed, Baihua Zheng, K. Zheng","doi":"10.1109/mdm.2019.00-94","DOIUrl":"https://doi.org/10.1109/mdm.2019.00-94","url":null,"abstract":"","PeriodicalId":241426,"journal":{"name":"2019 20th IEEE International Conference on Mobile Data Management (MDM)","volume":"6 1","pages":"0"},"PeriodicalIF":0.0,"publicationDate":"2019-06-01","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"134355949","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
TCSC: A New Type Of Spatial Crowdsourcing TCSC:新型的空间众包
2019 20th IEEE International Conference on Mobile Data Management (MDM) Pub Date : 2019-06-01 DOI: 10.1109/MDM.2019.00-24
Ting Wang
{"title":"TCSC: A New Type Of Spatial Crowdsourcing","authors":"Ting Wang","doi":"10.1109/MDM.2019.00-24","DOIUrl":"https://doi.org/10.1109/MDM.2019.00-24","url":null,"abstract":"The popularity of advanced mobile terminals allows spatial crowdsourcing to be widely used. In this work, we study a new type of spatial crowdsourcing, called time-continuous spatial crowdsourcing (TCSC in short). This type of crowdsourcing is primarily concerned with tasks that take a long time to finish and involves time-sharing among multiple workers. We study single-task and multi-task scenarios, and propose novel strategies to optimize the assignment process. Extensive experiments are conducted to support our proposals.","PeriodicalId":241426,"journal":{"name":"2019 20th IEEE International Conference on Mobile Data Management (MDM)","volume":"191 1","pages":"0"},"PeriodicalIF":0.0,"publicationDate":"2019-06-01","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"133297690","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
Mining Significant Co-Location Patterns From Spatial Regional Objects 从空间区域对象中挖掘重要的同位模式
2019 20th IEEE International Conference on Mobile Data Management (MDM) Pub Date : 2019-06-01 DOI: 10.1109/MDM.2019.00009
yurong Long, Peizhong Yang, Lizhen Wang
{"title":"Mining Significant Co-Location Patterns From Spatial Regional Objects","authors":"yurong Long, Peizhong Yang, Lizhen Wang","doi":"10.1109/MDM.2019.00009","DOIUrl":"https://doi.org/10.1109/MDM.2019.00009","url":null,"abstract":"A co-location pattern refers to the subset of features which frequently appear together in spatial proximity. There are many literatures studied the approach of discovering co-location patterns. However, a lot of proposed approaches need some thresholds given by the user, and it is difficult to give the proper thresholds. Moreover, most proposed approaches treat the spatial object as a point during the mining process, but spatial objects are dynamic or appear in the form of a cluster normally, which means that their locations are polygons rather than points. This paper provides a novel framework to mine co-location patterns from spatial regional objects. At first, we redefine the interest measure of significant co-locations. In our framework, the user does not need to specify any threshold, and the redefined interest measure is monotonically non-increasing which can be used for improving the mining efficiency. Then, an algorithm based on the grid partition is proposed to reduce time complexity further. Finally, we verify the efficiency and effectiveness of the proposed approach by extensive experiments.","PeriodicalId":241426,"journal":{"name":"2019 20th IEEE International Conference on Mobile Data Management (MDM)","volume":"32 1","pages":"0"},"PeriodicalIF":0.0,"publicationDate":"2019-06-01","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"131376814","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
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