Data storing and retrieving has been important since decades in the world of information. It makes this process prolific, when the retrieved information becomes smartly meaningful. Data mining is this new flavor. In the recent years data mining is a wide spread and active area of research. Its meaningfulness has gained momentum due to its vast area of applications. One of the popular and potent...

Mining for resources extraction may lead to geological and associated environmental changes due to ground movements, collision with mining cavities, and deformation of aquifers. Geological changes may continue in a reclaimed mine area, and the deformed aquifers may entail a breakdown of substrates and an increase in ground water tables, which may cause surface area inundation. Consequently, a r...

OBJECTIVE Blood lead level BLL and growth parameters including weight and height, in children, living in lead mining area was surveyed. METHODS Two groups of 7-11 yr old children, including 45 from a lead mining area (Angooran-Zanjan Province-Iran) and 36 from control area (similar area to the study area, but not lead mining: Ijrood--the same province), were selected to assess BLL (by atomic ...

Data mining is a non-trivial process. That is identifying novel, valid and potentially useful patterns in data. Data mining supports automatic data exploration. That is extracting hidden information from the huge database. Data mining refers to search useful and relevant information from the database. Spatial mining is a branch of data mining. The spatial mining deals with the location or geo-r...

With huge amount of information available online, the World Wide Web is fertile area of data mining research. The web mining research is crossroad of several forms of several research communities such as data base IR within AI, especially the subarea of Machine language and Natural Language processing. However there is lot of confusion with comparing research efforts from different point of vie...

There is a long tradition of describing cities through a focus on the characteristics of their residents. A brief review of the history of this approach to describing cities highlights some persistent challenges. To fit within the constraints of widely used multivariate data reduction techniques and thematic cartography populations are classified. Historically, this classification has been guid...

In the past twenty years, agents (we mean autonomous agent and multi-agent systems) and data mining (also knowledge discovery) have emerged separately as two of most prominent, dynamic and exciting research areas. In recent years, an increasingly remarkable trend in both areas is the agent-mining interaction and integration. This is driven by not only researcher’s interests, but intrinsic chall...

In the past, many researchers used data mining techniques in any area. A lot of amounts of data have been collected from scientific domains such as geo sciences, astronomy, meteorology, geology and biological sciences. Data mining techniques and tools used by researchers in biological and environmental problems also. In biological science data mining used in sequences alignment is based on the ...

In the area of Data Mining ,Image Mining technology has been considered an advanced field for discovering information related to the images.Image Mining is a process of extracting knowledge concerning images.The demand of image mining increases as the need of image data is growing day by day.There are many techniques developed in the earlier researches and eventually these techniques can reveal...

One of the most valuable assets of an organization is its organizational data. The analysis and mining of this potential hidden treasure can lead to much added-value for the organization. Process mining is an emerging area that can be useful in helping organizations understand the status quo, check for compliance and plan for improving their processes. The aim of process mining is to extract kn...