An Overview of Data Mining Techniques

This overview provides a description of some of the most common data mining algorithms in use today.   We have broken the discussion into two sections, each with a specific theme:

• Classical Techniques: Statistics, Neighborhoods and Clustering
• Next Generation Techniques: Trees, Networks and Rules

Each section will describe a number of data mining algorithms at a high level, focusing on the "big picture" so that the reader will be able to understand how each algorithm fits into the landscape of data mining techniques.   Overall, six broad classes of data mining algorithms are covered.  Although there are a number of other algorithms and many variations of the techniques described, one of the algorithms from this group of six is almost always used in real world deployments of data mining systems.

Data Preprocessing

Stages in performing data mining one of them is data preprocessing. The question is why the data needs to be cleaned before it is processed?
This happens because usually the data to be used has not been good, the cause include:
- Incomplete : lack of values ​​of certain attributes or other attributes.
- Noisy : containing errors or outliers values ​​that deviate from the expected.
- Inconsisten : mismatch in the use of code or name.
Here are good quality data was based on good decisions and data warehouse needs consistent integration of quality data.

The concept of Data Mining

What actually motivates Data mining and why data mining is so important ?

The main reason why data mining is very interesting information industry in recent years is due to the availability of large amounts of data and the magnitude of the need to transform data into useful information and knowledge.

Data mining is the activity of extracting or mining knowledge from data size / large numbers, this is information that will be very useful for development. Where the steps to perform data mining is as follows :

Application of Data Mining

As a new branch of science in the areas of computers quite a lot of applications that can do by Data Mining. Moreover, supported by the richness and diversity of the various fields of science (artificial intelligence, databases, statistics, mathematical modeling, image processing, etc..) Makes the application of data mining becomes more widespread. In any field application of data mining can be done? This brief article attempts to answer.

Data Mining and Web Mining

Data mining (DM), also known as Knowledge Discovery (Frawley et al., 1992), is one of the rapidly growing field due to the large demand for value-added of large-scale database that accumulates more in line with the growth of information technology. In general, data mining can be defined as a series of processes to explore the added value of science, which is not known manually from a data set (Pramudiono, 2003).Web mining is the application of data mining techniques to the web in order to acquire knowledge and information over the web. Web mining can be categorized into three different scope, namely Web content mining, web structure mining and web usage mining (Srivastava et al., 2000).

Data Mining

Data Mining is one branch of computer science is relatively new. And until now people are still debating to put data mining in the area of ​​science which, because of data mining involving databases, artificial intelligence (artificial intelligence), statistics, etc.. There are those who argue that data mining is nothing more than machine learning or statistical analysis that runs on the database. Yet others argue that the database is an important role in data mining because data mining to access data whose size is large (up to terabytes) and it seemed particularly important role in database query optimization it.

How to Improve Website Ranking with easy

Search engine optimization (SEO) involves taking steps to help a website index higher in the search engines for the purpose of increasing organic traffic to the site. Organic traffic represents website visitors are those who find their way to a particular site as the result of running a search engine inquiry rather than because they click on an advertisement.
Each search engine uses a different algorithm to determine search engine ranking. One of the first steps in figuring out how to improve web page ranking is to develop an understanding of what search algorithms work and using that knowledge to develop and market your website.