Textually Relevant Spatial Skylines

Textually Relevant Spatial Skylines
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文本相关的空间天际线

DOI:
10.1109/tkde.2015.2465374
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发表时间:
2016
期刊:
IEEE Trans. Knowl. Data Eng.
影响因子:
--
通讯作者:
Nikos Mamoulis
Nikos Mamoulis
中科院分区:
其他
文献类型:
--
作者:
Jieming Shi;Dingming Wu;Nikos Mamoulis

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我们研究了空间文本天际线(STS)查询的建模和评估,其中选择天际线点不仅基于它们与一组查询位置的距离,而且还基于它们与一组查询关键字的相关性。 STS是Espe
We study the modeling and evaluation of a spatio-textual skyline (STS) query, in which the skyline points are selected not only based on their distances to a set of query locations, but also based on their relevance to a set of query keywords. STS is especially relevant to modern applications, where points of interest are typically augmented with textual descriptions. We investigate three models for integrating textual relevance into the spatial skyline. Among them, model STD, which combines spatial distance with textual relevance in a derived dimensional space, is found to be the most effective one. STD computes a skyline which not only satisfies the intent of STS, but also has a small and easy-to-interpret size. We propose an efficient algorithm for computing STD-based skylines, which operates on an IR-tree that indexes the data. The effectiveness of our STD model and the efficiency of the proposed algorithm are evaluated on real data sets.
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