Spatial and Spatiotemporal Data Mining: Recent Advances
نویسندگان
چکیده
Explosive growth in geospatial data and the emergence of new spatial technologies emphasize the need for automated discovery of spatial knowledge. Spatial data mining is the process of discovering interesting and previously unknown, but potentially useful patterns from large spatial databases. The complexity of spatial data and intrinsic spatial relationships limits the usefulness of conventional data mining techniques for extracting spatial patterns. In this chapter we explore the emerging field of spatial data mining, focusing on four major topics: prediction and classification, outlier detection, co-location mining, and clustering. Spatiotemporal data mining is also briefly discussed.
منابع مشابه
Spatial and Spatiotemporal Data Mining
The significant growth of spatial and spatiotemporal data collection as well as the emergence of new technologies have heightened the need for automated discovery of spatiotemporal knowledge. Spatial and spatiotemporal data mining techniques are crucial to organizations which make decisions based on large spatial and spatiotemporal datasets. The interdisciplinary nature of spatial and spatiotem...
متن کاملDecentralized spatial data mining for geosensor networks
Advances in distributed sensing and computing technology offer new, reliable, and costeffective means to collect fine-grained spatiotemporal data. Conventional spatiotemporal data mining procedures, however, are based on centralized models of information processing, where sophisticated and powerful central systems collate and process global information. By contrast, decentralized spatial comput...
متن کاملSensing for Mobile Objects
Recent advances in affordable positioning hardware and software have made the availability of location data ubiquitous. Personal devices such as tablet PCs, smart phones and even sport watches are all able to collect and store a user’s location over time, providing an ever-growing supply of spatiotemporal data. Managing this plethora of data is a relatively new challenge and there has been a gr...
متن کاملSpatio-Temporal Data Mining: From Big Data to Patterns
Technological advances in terms of data acquisition enable to better monitor dynamic phenomena in various domains (areas, fields) including environment. The collected data is more and more complex spatial, temporal, heterogeneous and multi-scale. Exploiting this data requires new data analysis and knowledge discovery methods. In that context, approaches aimed at discovering spatio-temporal patt...
متن کاملUnsupervised Topographic Learning for Spatiotemporal Data Mining
In recent years, the size and complexity of datasets have shown an exponential growth. In many application areas, huge amounts of data are generated, explicitly or implicitly containing spatial or spatiotemporal information. However, the ability to analyze these data remains inadequate, and the need for adapted data mining tools becomes a major challenge. In this paper, we propose a new unsuper...
متن کامل