Spatial Database and Data Mining

Our group focusses on developing methods for storing querying, analyzing and mining very large geo-spatial datasets. For graph structured data (e.g. roadmaps), our group designed a novel storage method which is faster than traditional spatial indices. In querying area, our group has developed methods to process direction based predicates as well as methods to exploit parallel computers for answering spatial queries. In analysis and data mining, we are exploring computationally-efficient methods of modelling spatial auto-correlation which violates the independent identical distribution assumption made by data mining techniques based on classical statistics. We are exploring new data mining methods which can model auto-correlation and can scale up to large datasets.

Favourite Quotes: Computer Science Research

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