Applying spatial database techniques to other domains: A case study on top-k and computational geometric operators
In this seminar, we will explore how processing rich spatial data is not the only practical (and research-wise promising) application domain for traditional spatial database techniques. An equally promising direction, possibly with low-hanging fruits for research innovation, may be to apply the spat...
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| Format: | text |
| Language: | English |
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Institutional Knowledge at Singapore Management University
2018
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| Online Access: | https://ink.library.smu.edu.sg/sis_research/4156 https://ink.library.smu.edu.sg/context/sis_research/article/5160/viewcontent/p25_Mouratidis.pdf |
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| Institution: | Singapore Management University |
| Language: | English |
| Summary: | In this seminar, we will explore how processing rich spatial data is not the only practical (and research-wise promising) application domain for traditional spatial database techniques. An equally promising direction, possibly with low-hanging fruits for research innovation, may be to apply the spatial data management expertise of our community to non-spatial types of queries, and to extend standard, more theoretical operators to large scale datasets with the objective of practical solutions (as opposed to favorable asymptotic complexity alone). As a case study, we will review spatial database work on top-k-related operators (i.e., non-spatial problems) and how it integrates fundamental computational geometric operators with spatial indexing/pruning to produce efficient solutions to practical problems. |
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