COAL MINING GEOSPATIAL DATA FOR THE NATION

Modeling Spatial Dependencies for Mining Geospatial Data

Widespread use of spatial databases[24] is leading to an increasing interest in mining interesting and useful but implicit spatial patterns[14, 17, 10, 22]. Efficient tools for extracting information from geo-spatial data, the focus of this work, are crucial to organizations which make decisions based on large spatial data sets. These organizations are spread across many domains including ecolo...

Geospatial Data Mining and Knowledge Discovery

The advent of remote sensing and survey technologies over the last decade has dramatically enhanced our capabilities to collect terabytes of geographic data on a daily basis. However, the wealth of geographic data cannot be fully realized when information implicit in data is difficult to discern. This confronts GIScientists with an urgent need for new methods and tools that can intelligently an...

Mining Geospatial Data in a Transductive Setting

Many organizations collects large amounts of spatially referenced data. Spatial Data Mining targets the discovery of interesting, implicit knowledge from such data. The specific classification task has been extensively investigated in the classical inductive setting, where only labeled examples are used to generate a classifier, discarding a large amount of information potentially conveyed by t...

Data Structuration in Coal Research and Coal Mining

the clustering and classification data mining techniques in insurance fraud detection:the case of iranian car insurance

با توجه به گسترش روز افزون تقلب در حوزه بیمه به خصوص در بخش بیمه اتومبیل و تبعات منفی آن برای شرکت های بیمه، به کارگیری روش های مناسب و کارآمد به منظور شناسایی و کشف تقلب در این حوزه امری ضروری است. درک الگوی موجود در داده های مربوط به مطالبات گزارش شده گذشته می تواند در کشف واقعی یا غیرواقعی بودن ادعای خسارت، مفید باشد. یکی از متداول ترین و پرکاربردترین راه های کشف الگوی داده ها استفاده از ر...