Skyline queries are extensively incorporated in various real-life applications by filtering uninteresting data objects.Sometimes,a skyline query may return so many results because it cannot control the retrieval condi...Skyline queries are extensively incorporated in various real-life applications by filtering uninteresting data objects.Sometimes,a skyline query may return so many results because it cannot control the retrieval conditions especially for highdimensional datasets.As an extension of skyline query,the kdominant skyline query reduces the control of the dimension by controlling the value of the parameter k to achieve the purpose of reducing the retrieval objects.In addition,with the continuous promotion of Bigdata applications,the data we acquired may not have the entire content that people wanted for some practically reasons of delivery failure,no power of battery,accidental loss,so that the data might be incomplete with missing values in some attributes.Obviously,the k-dominant skyline query algorithms of incomplete data depend on the user definition in some degree and the results cannot be shared.Meanwhile,the existing algorithms are unsuitable for directly used to the incomplete big data.Based on the above situations,this paper mainly studies k-dominant skyline query problem over incomplete dataset and combines this problem with the distributed structure like MapReduce environment.First,we propose an index structure over incomplete data,named incomplete data index based on dominate hierarchical tree(ID-DHT).Applying the bucket strategy,the incomplete data is divided into different buckets according to the dimensions of missing attributes.Second,we also put forward query algorithm for incomplete data in MapReduce environment,named MapReduce incomplete data based on dominant hierarchical tree algorithm(MR-ID-DHTA).The data in the bucket is allocated to the subspace according to the dominant condition by Map function.Reduce function controls the data according to the key value and returns the k-dominant skyline query result.The effective experiments demonstrate the validity and usability of our index structure and the algorithm.展开更多
At present,most k-dominant Skyline query algorithms are oriented to static datasets,this paper proposes a k-dominant Skyline query algorithm for dynamic datasets.The algorithm is recursive circularly.First,we compute ...At present,most k-dominant Skyline query algorithms are oriented to static datasets,this paper proposes a k-dominant Skyline query algorithm for dynamic datasets.The algorithm is recursive circularly.First,we compute the dominant ability of each object and sort objects in descending order by dominant ability.Then,we maintain an inverted index of the dominant index by k-dominant Skyline point calculation algorithm.When the data changes,it is judged whether the update point will afect the k dominant Skyline point set.So the k-dominant Skyline point of the new data set is obtained by inserting and deleting algorithm.The proposed algorithm resolves maintenance isue of a frequently updated database by dynamically updating the data sets.The experimental results show that the query algorithm can efectively improve query eficiency.展开更多
在移动互联网环境下,空间文本skyline查询可以有效支持用户在空间和关键词方面的查询。随着需求的多样性,基于用户经常会同时考虑空间距离、数值型信息、关键词和时间等因素对查询结果的影响,提出了基于时间的空间文本关键词skyline查询...在移动互联网环境下,空间文本skyline查询可以有效支持用户在空间和关键词方面的查询。随着需求的多样性,基于用户经常会同时考虑空间距离、数值型信息、关键词和时间等因素对查询结果的影响,提出了基于时间的空间文本关键词skyline查询(Time based Spatial Text Keyword Skyline Query,TSTKSQ),用来查找在空间、数值、关键词和时间都满足条件的优秀对象,设计了基于时间的空间文本关键词skyline查询的索引结构STTR-Tree,提出了关键词、时间和时空关键词相关性的评价函数,在裁剪策略的基础上提出了skyline查询算法。通过实验结果分析,验证了算法的准确性和有效性。展开更多
基金This work was supported by the National Natural Science Foundation of China(Grant Nos.62072220,61802160,61502215)China Postdoctoral Science Foundation Funded Project(2020M672134)+1 种基金Science Research Fund of Liaoning Province Education Department(LJC201913)Doctor Research Start-up Fund of Liaoning Province(20180540106).
文摘Skyline queries are extensively incorporated in various real-life applications by filtering uninteresting data objects.Sometimes,a skyline query may return so many results because it cannot control the retrieval conditions especially for highdimensional datasets.As an extension of skyline query,the kdominant skyline query reduces the control of the dimension by controlling the value of the parameter k to achieve the purpose of reducing the retrieval objects.In addition,with the continuous promotion of Bigdata applications,the data we acquired may not have the entire content that people wanted for some practically reasons of delivery failure,no power of battery,accidental loss,so that the data might be incomplete with missing values in some attributes.Obviously,the k-dominant skyline query algorithms of incomplete data depend on the user definition in some degree and the results cannot be shared.Meanwhile,the existing algorithms are unsuitable for directly used to the incomplete big data.Based on the above situations,this paper mainly studies k-dominant skyline query problem over incomplete dataset and combines this problem with the distributed structure like MapReduce environment.First,we propose an index structure over incomplete data,named incomplete data index based on dominate hierarchical tree(ID-DHT).Applying the bucket strategy,the incomplete data is divided into different buckets according to the dimensions of missing attributes.Second,we also put forward query algorithm for incomplete data in MapReduce environment,named MapReduce incomplete data based on dominant hierarchical tree algorithm(MR-ID-DHTA).The data in the bucket is allocated to the subspace according to the dominant condition by Map function.Reduce function controls the data according to the key value and returns the k-dominant skyline query result.The effective experiments demonstrate the validity and usability of our index structure and the algorithm.
基金The authors are grateful to the editors and reviewers for their helpful comments and suggestions.This research was partially supported by National Key R&D Program of China(2018********01)National Social Science Foundation project(17BXW065)+1 种基金Science and Technology Research project of Henan province(172102310628,162102310616)Science and Technology Research project of Zhengzhou(141PPTGG368).
文摘At present,most k-dominant Skyline query algorithms are oriented to static datasets,this paper proposes a k-dominant Skyline query algorithm for dynamic datasets.The algorithm is recursive circularly.First,we compute the dominant ability of each object and sort objects in descending order by dominant ability.Then,we maintain an inverted index of the dominant index by k-dominant Skyline point calculation algorithm.When the data changes,it is judged whether the update point will afect the k dominant Skyline point set.So the k-dominant Skyline point of the new data set is obtained by inserting and deleting algorithm.The proposed algorithm resolves maintenance isue of a frequently updated database by dynamically updating the data sets.The experimental results show that the query algorithm can efectively improve query eficiency.
文摘在移动互联网环境下,空间文本skyline查询可以有效支持用户在空间和关键词方面的查询。随着需求的多样性,基于用户经常会同时考虑空间距离、数值型信息、关键词和时间等因素对查询结果的影响,提出了基于时间的空间文本关键词skyline查询(Time based Spatial Text Keyword Skyline Query,TSTKSQ),用来查找在空间、数值、关键词和时间都满足条件的优秀对象,设计了基于时间的空间文本关键词skyline查询的索引结构STTR-Tree,提出了关键词、时间和时空关键词相关性的评价函数,在裁剪策略的基础上提出了skyline查询算法。通过实验结果分析,验证了算法的准确性和有效性。
