Data mining is actually the process of collecting data from different sources and then interpreting it and finally converting it into useful information which helps in increasing the revenue, curtailing costs thereby providing a competitive edge to the organisation. Excerpt Data Mining für Marketing:...
A data mining model is a virtual structure in the field of computer science that represents grouped data for predictive analysis. It is different from data tables as it interprets data and stores statistical information about the rules and patterns learned from training the model. The model is ...
a database implementation (schema) from a data model is termedphysical database design. In short, the data model defines what data must be represented in the application and the database schema defines how that data is stored. The goal ofdata modeling, also termedconceptual database design, ...
My goal is to provide a high-level overview. Three Options for Creating a Conceptual Model The Entity Framework relies on a conceptual model of your domain entities, called an Entity Data Model (EDM), and choosing how to create that model is the first decision you’ll need to make. There...
Therefore, argumentation mining is an important part of a complete argumentation analysis, i.e. understanding the content of serial arguments, their linguistic structure, the relationship between the preceding and following arguments, recognizing the underlying conceptual beliefs, and understanding within ...
Figure 1** Entity Framework Overview ** These data access techniques allow you to interact with the conceptual entities defined within the entity model rather than the objects of a physical store such as a relational database. The data model and associated mappings are created by using either th...
This Object Relational Mapping (ORM) framework uses LINQ to abstract a database schema and presents it to an application as a conceptual schema. Like the DataSet, this technology also minimized the need to work directly with SQL. However, it still requ...
The purpose of this collection is to present traditional and contemporary conceptual work and research pertaining to the issue of education and stratification. The readings highlight major themes and give the reader a good overview of the area. The organization of readings parallels the conceptual ...
Arelational data-mining modelis used for mining data from a relational database. This mining model is best used when working with rapidly changing data. In suchenvironments, it might not be feasible to create a dimensional database from the relational model on a regular basis. Think of a cal...
Data mining emerged as a distinct field in the 1990s, but you can trace its conceptual roots back to the mid-20th century. The original term for data mining was "knowledge discovery in databases" or KDD. The approach evolved as a response to the advent of large-scale data storage (e.g...