Geo-spatial Big Data Mining Techniques
نویسنده
چکیده
As stated in literature by several authors, there has been literally big-bang explosion in data acquired in recent times. This is especially so about the geographical or geospatial data. The huge volume of data acquired in different formats, structured, unstructured ways, having large complexity and non-stop generation of these data have posed an insurmountable challenge in scientific and business world alike. The conventional tools, techniques and hardware existing about a decade ago have met with the limitations in handling such data. Hence, such data are termed as big data. This has necessitated inventing new software tools and techniques as well as parallel computing hardware architectures to meet the requirement of timely and efficient handling of the big data. The field of data mining has been benefitted from these evolutions as well. This article reviews the evolution of data mining techniques over last two decades and efforts made in developing big data analytics, especially as applied to geospatial big data. This is still a very actively evolving field. There will be no surprise if some new techniques are published before this article appears in print.
منابع مشابه
Data Mining Approaches for Geo-Spatial Big Data: Uncertainty Issues
The availability of a vast amount of heterogeneous information from a variety of sources ranging from satellite imagery to the Internet has been termed as the problem of Big Data. Currently there is a great emphasis on the huge amount of geophysical data that has a spatial basis or spatial aspects. To effectively utilize such volumes of data, data mining techniques are needed to manage discover...
متن کاملA High Performance, Spatiotemporal Statistical Analysis System Based on a Spatiotemporal Cloud Platform
With the increase in size and complexity of spatiotemporal data, traditional methods for performing statistical analysis are insufficient for meeting real-time requirements for mining information from Big Data, due to both dataand computing-intensive factors. To solve the Big Data challenges in geostatistics and to support decision-making, a high performance, spatiotemporal statistical analysis...
متن کاملPixel Based Visual Mining of Geo-Spatial Data
In many application domains, data is collected and referenced by geo-spatial location. Spatial data mining, or the discovery of interesting patterns in such databases, is an important capability in the development of database systems. A noteworthy trend is the increasing size of data sets in common use, such as records of business transactions, environmental data and census demographics. These ...
متن کاملEfficient Rule Discovery in a Geo-spatial Decision Support System
This paper describes the application of data mining techniques in a Geo-spatial Decision Support System, which focuses on drought risk management. Association rule discovery is one of the widely used approaches in data mining. This paper highlights the rule discovery algorithms that we have developed and used for discovering useful patterns in ocean parameters and climatic indices to monitor dr...
متن کاملA Novel Popular Tourist Attraction Discovering Approach Based on Geo-Tagged Social Media Big Data
In the big data era, the social media data that contain users’ geographical locations are growing explosively. These kinds of spatiotemporal data provide a new perspective for us to observe the human movement behavior. By mining such spatiotemporal data, we can incorporate the users’ collective wisdom, build novel services and bring convenience to people. Through spatial clustering of the origi...
متن کاملذخیره در منابع من
با ذخیره ی این منبع در منابع من، دسترسی به آن را برای استفاده های بعدی آسان تر کنید
عنوان ژورنال:
دوره شماره
صفحات -
تاریخ انتشار 2016