Web Mining is the use of data mining techniques to automatically detect web documents and services, extract information from web resources, and identify common patterns on the Internet.
Web Mining occurs in the following stages:
- input stage – getting “raw” data (server logs, text electronic documents);
- preprocessing stage – data is presented in a form necessary for the successful construction of a model;
- pattern discovery stage;
- pattern analysis stage – the interpretation of the results.
This is the general steps, which are necessary to go through to analyze data on the Internet. Specific procedures for each step depend on the task.
In connection with this, there are various categories of Web Mining:
- Web Content Mining;
- Web Structure Mining;
- Web Usage Mining.
Web Content Mining is a process of the knowledge extraction from the web documents or their descriptions available on the internet. The search for the knowledge on the Internet is difficult and time consuming task. This is what Web Content Mining is dealing with. It is based on a combination of features of information retrieval, machine learning, and data mining.
Web Structure Mining is a process of finding structural information on the Internet. This type of mining examines the relationship between web pages based on the connections between them.
The constructed models can be used to categorize and find similar web resources, and for detecting copyright sites.
Web Usage Mining is the automatic detection of patterns in the path of the user movement and the associated data collected or acquired as a result of interaction with one or more web sites. This direction is based on the extraction of data from the Web server logs. The purpose of the analysis is to identify the preferences of the visitors using those or other resources on the Internet.
Students writing their research proposals on the subject have know that data mining technology has helped e-commerce create personalized marketing, which ultimately led to an increase in trading volume. Companies can establish a closer relationship with customers by providing them exactly what they need. Companies can better understand customer needs and respond more quickly to customer it. Companies can find, attract, and retain customers, save on production costs by using the acquired understanding of the requirements of the customer. Companies improve profitability through targeted pricing based on profiles created. In addition, government agencies use this technology for the classification of threats and fight against terrorism.
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