Sentence examples for data mining knowledge from inspiring English sources

By collecting knowledge or information from conditions and the goal, we choose several knowledge as seed, then distribute it to all the department leaders, let them input relative knowledge including data mining knowledge to the platform.

Our paper aims to encourage those research scientists which do not have extensive programming and data mining knowledge to take advantage of existing data mining tools, to embrace classical data mining and LOD approaches in support of gaining more insight and recognizing patterns in highly complex data sets.

To find an optimised design of the target-machine, this means to find the minimum number of supports and gears as well as the optimised configuration of the multi-spindle drilling gears, an automated system based on data mining, knowledge discovery and automated decision process is explained.

Participants who identified as directors viewed analytics as the process of data mining, knowledge discovery, and extraction of information.

This course prepares students for advanced study of data fusion, data mining, knowledge base construction, problem-solving methodologies of "intelligent agents" and the design of intelligent control systems.

Data mining knowledge, as a logical process for finding useful data through large amount of data, and particularly regression technique can be used for modeling the relationship between one or more independent variables and dependent variables (Ramageri 2010).

A software platform for data-mining knowledge discovery process generally involves 3-components i.e. data repository, data-mining knowledge discovery engine, query interface [12, 39].

In this study, a novel approach is proposed that is based upon the integration of conventional usability testing and heuristic evaluation with data-mining knowledge discovery process.

This extraction process in data-mining knowledge discovery [12, 39] is decomposed into four main processes (a) data pre-processing, (b) data-mining, (c) pattern identification and (d) graphical representation.

It is important to note that data-mining is the most vital step in data-mining knowledge discovery process since it extracts previously unknown information and identifies hidden patterns of information for evaluation of patterns [39].

In developing this architecture, which is very useful for agricultural decision support systems, we considered web based large-scale dynamic data mining, contextual knowledge extraction, and integrated knowledge representation methods.