Fast Identification of Interesting Spatial Regions with Applications in Human Development Research

Autor:	M. Satish Kumar, Carl Duffy, Deepak P, Amaresh Dubey, Amit Thorat, Cheng Long
Rok vydání:	2018
Předmět:	business.industry Computer science 020209 energy 0202 electrical engineering electronic engineering information engineering Domain knowledge 02 engineering and technology Artificial intelligence business Machine learning computer.software_genre computer Spatial analysis Human development (humanity)
Zdroj:	Lecture Notes in Computer Science ISBN: 9783319988115 DEXA (2)
Popis:	Large-scale demographic datasets with spatial information provide a rich platform for human development research. Much emphasis is often placed on understanding deviations from dataset-level behavior across demographic attributes within spatially coherent regions, since those could point to a local condition worth addressing through regional policies, or at the other extreme, a less known success story that offers new learnings. Inspired by such scenarios, we build upon domain knowledge from HDR to devise an interestingness scoring for spatial regions and formulate the computational task of interesting spatial region identification. Accordingly, we develop a taxonomic organization of spatial regions and formulate bounds on interestingness scores, which are then leveraged to develop an efficient technique to address the task. Our search method is empirically evaluated over two real-world datasets, and is seen to record orders of magnitude of response time improvements over region enumeration. The absolute response times and the memory overheads of our approach are seen to be within highly desirable ranges, establishing the effectiveness of our solution for the task.
Databáze:	OpenAIRE
Externí odkaz:	https://explore.openaire.eu/search/publication?articleId=doi_________::b030cddbae8fa1e463c102431d31ca97 https://doi.org/10.1007/978-3-319-98812-2_37 Zobrazit plný text záznamu