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| 1 | Continuous ranking on uncertain streams显示文摘数据无常广泛地在许多网应用,金融应用和传感器网络存在。与最大的评价分数返回很多个元组的评价询问在数据库管理的域里是重要的。大多数存在工作集中于为各种各样的评价建议静态的答案在不明确的数据上的语义。我们的焦点是处理连续的在不明确的数据流上评价询问:严峻的各新的元组将输出高度评价的元组。当新元组到达时,主要挑战来自可能的世界空间将指数地种的事实不仅,而且为低空间复杂性和时间复杂性到的要求适应流的环境。这份报纸在不明确的数据溪流上在处理连续评价瞄准询问。我们首先学习怎么确切处理这个问题,然后,我们建议一个新奇方法(指数的采样) 估计一个元组的期望的等级与高质量。在理论和详细试验性的报告的分析评估建议方法。 | Cheqing JIN Jingwei ZHANG Aoying ZHOU | 2012 | Frontiers of Computer Science2012，6，6： | 3 |
| 2 | Sliding-window top-k queries on uncertain streams 显示文摘 | Jin Cheqing Yi Ke Chen Li | 2010 | VLDB Journal2010，19，3： | 1 |
| 3 | A framework for cloned vehicle detection显示文摘Rampant cloned vehicle offenses have caused great damage to transportation management as well as public safety and even the world economy.It necessitates an efficient detection mechanism to identify the vehicles with fake license plates accurately,and further explore the motives through discerning the behaviors of cloned vehicles.The ubiquitous inspection spots that deployed in the city have been collecting moving information of passing vehicles,which opens up a new opportunity for cloned vehicle detection.Existing detection methods cannot detect the cloned vehicle effectively due to that they use the fixed speed threshold.In this paper,we propose a two-phase framework,called CVDF,to detect cloned vehicles and discriminate behavior patterns of vehicles that use the same plate number.In the detection phase,cloned vehicles are identified based on speed thresholds extracted from historical trajectory and behavior abnormality analysis within the local neighborhood.In the behavior analysis phase,consider the traces of vehicles that uses the same license plate will be mixed together,we aim to differentiate the trajectories through matching degree-based clustering and then extract frequent temporal behavior patterns.The experimental results on the real-world data show that CVDF framework has high detection precision and could reveal cloned vehicles’behavior effectively.Our proposal provides a scientific basis for traffic management authority to solve the crime of cloned vehicle. | Minxi Li Jiali Mao Xiaodong Qi Cheqing Jin | 2020 | Frontiers of Computer Science2020，14，5： | 1 |
| 4 | Computing rarity on uncertain data显示文摘The essence of uncertain data management has been well adopted since data uncertainty widely exists in lots of applications,such as Web,sensor networks,etc.Most of the uncertain data models are based on the possible world semantics.Because the number of the possible worlds will blowup exponentially with the growth of the data set,it is much more challenging to handle uncertain data than deterministic data.In this paper,we take the first attempt to study the rarity,an important statistic that describes the proportion of items with the same frequency,upon uncertain data.We have proposed three novel solutions,including an exact method and an approximate method to compute the rarity of a given frequency respectively,and a method to find the frequency of the maximum rarity.Analysis in theorem and extensive experimental results demonstrate the effectiveness and efficiency of the proposed solutions. | JIN CheQing ZHOU MinQi ZHOU AoYing | 2011 | Science China(Information Sciences)2011，54，10： | 1 |
| 5 | A survey of uncertain data management technology research显示文摘 | Zhou Aoying Jin Cheqing Wang Guoren | 2009 | Chinese Journal of Computers2009，32，1： | 1 |
| 6 | MapReduce-based entity matching with multiple blocking functions显示文摘 | Cheqing JIN Jie CHEN Huiping LIU | 2017 | Frontiers of Computer Science2017，11，5： | 1 |
| 7 | Efficient clustering of uncertain data streams显示文摘 | Cheqing Jin Jeffrey Xu Yu Aoying Zhou etal | 2013 | Knowledge and Information Systems2013，，： | 1 |
| 8 | Popular route planning with travel cost estimation from trajectories显示文摘With the increasing number of GPS-equipped vehicles,more and more trajectories are generated continuously,based on which some urban applications become feasible,such as route planning.In general,popular route that has been travelled frequently is a good choice,especially for people who are not familiar with the road networks.Moreover,accurate estimation of the travel cost(such as travel time,travel fee and fuel consumption)will benefit a wellscheduled trip plan.In this paper,we address this issue by finding the popular route with travel cost estimation.To this end,we design a system consists of three main components.First,we propose a novel structure,called popular traverse graph where each node is a popular location and each edge is a popular route between locations,to summarize historical trajectories without road network information.Second,we propose a self-adaptive method to model the travel cost on each popular route at different time interval,so that each time interval has a stable travel cost.Finally,based on the graph,given a query consists of source,destination and leaving time,we devise an efficient route planning algorithmwhich considers optimal route concatenation to search the popular route from source to destination at the leaving time with accurate travel cost estimation.Moreover,we conduct comprehensive experiments and implement our system by a mobile App,the results show that our method is both effective and efficient. | Huiping LIU Cheqing JIN Aoying ZHOU | 2020 | Frontiers of Computer Science2020，14，1： | 1 |
| 9 | Sliding-window top-k queries on uncertain streams显示文摘 | Jin Cheqing Yi Ke Chen Lei | 2008 | Proceedings of the VLDB Endowment2008，1，1： | 1 |
| 10 | Sliding-Window Top-k Queries on Uncertain Streams显示文摘 | Cheqing Jin Ke Yi Lei Chen | | 0，，01： | 1 |
| 11 | Benchmarking in-memory database显示文摘 | Cheqing JIN Yangxin KONG Qiangqiang KANG Weining QIAN Aoying ZHOU | 2016 | Frontiers of Computer Science2016，10，6： | 0 |
| 12 | A privacy-enhancing scheme against contextual knowledge-based attacks in location-based services显示文摘1 Introduction and main contributions Location-based services are springing up around us,while leakages of users'privacy are inevitable during services.Even worse,adversaries may analyze intercepted service data,and extract more privacy like health and property.Therefore,privacy preservation is an indispensable guarantee on LBS security.Among the previous approaches to privacy preservation,k-anonymity-based ones have drawn much research attention[1-3].However,some privacy concern will be aroused if these schemes are adopted directly.For instance,Ut issues a query'Find the nearest hotel around me'in such an area as Fig.1(privacy profile k=4).DLS algorithm[2]constructs anonymity set A because these four cells have similar probabilities of being queried in the past.However,experienced adversaries can exclude some cells if they have learned rich contextual knowledge(side information)from historical data,such as features of each cell and LBS users. | Jiaxun HUA Yu LIU Yibin SHEN Xiuxia TIAN Yifeng LUO Cheqing JIN | 2020 | Frontiers of Computer Science2020，14，3： | 0 |
| 13 | Distributed top-k similarity query on big trajectory streams显示文摘Recently, big trajectory data streams are generated in distributed environments with the popularity of smartphones and other mobile devices. Distributed top?k similarity query, which finds k trajectories that are most similar to a given query trajectory from all remote sites, is critical in this field. The key challenge in such a query is how to reduce the communication cost due to the limited network bandwidth resource. Although this query can be solved by sending the query trajectory to all the remote sites, in which the pairwise similarities are computed precisely. However, the overall cost, O(n·m),is huge when nor mis huge, where n is the size of query trajectory and m is the number of remote sites. Fortunately, there are some cheap ways to estimate pairwise similarity, which filter some trajectories in advance without precise computation. In order to overcome the challenge in this query, we devise two general frameworks, into which concrete distance measures can be plugged. The former one uses two bounds (the upper and lower bound), while the latter one only uses the lower bound. Moreover, we introduce detailed implementations of two representative distance measures, Euclidean and DTW distance, after inferring the lower and upper bound for the former framework and the lower bound for the latter one. Theoretical analysis and extensive experiments on real-world datasets evaluate the efficiency of proposed methods. | Zhigang ZHANG Xiaodong QI Yilin WANG Cheqing JIN Jiali MAO Aoying ZHOU | 2019 | Frontiers of Computer Science2019，13，3： | 0 |
| 14 | Online clustering of streaming trajectories显示文摘 | Jiali MAO Qiuge SONG Cheqing JIN Zhigang ZHANG Aoying ZHOU | 2018 | Frontiers of Computer Science2018，12，2： | 0 |
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