What are the rules of web usage mining?

Data MiningDatabaseData Structure

Web mining defines the process of using data mining techniques to extract beneficial patterns trends and data generally with the help of the web by dealing with it from web-based records and services, server logs, and hyperlinks. The objective of web mining is to find the designs in web records by collecting and analyzing information to get essential insights.

Web mining can be viewed as the software of adapted data mining approaches to the internet, whereas data mining is defined as the application of the algorithm to discover patterns on generally structured data fixed into a knowledge discovery process.

Web mining has distinctive features to offer a set of multiple data types. The web has multiple elements that yield multiple approaches for the mining procedure, including web pages including text, web pages are linked via hyperlinks, and customer activity can be monitored via web server logs.

There are various rules of web usage mining which are as follows −

Preprocessing − The web usage log is not in a format that is accessible by mining applications. For some data to be used in a mining application, the data can be required to be reformatted and cleansed. There are some issues specifically related to the use of weblogs. There are some steps included in the processing phase include cleansing, user identification, session identification, path completion, and formatting.

Data structure − There are several unique data structures have been proposed to keep track of patterns identified during the web usage mining process. A basic data structure that is used is called a tree. A tree is a rooted tree, where each path from the root to a leaf represents a sequence. Trees can save strings for pattern matching applications. The only problem with trees is space requirements.

Pattern discovery − The most common data mining technique used on clickstream data is that of uncovering traversal patterns. A traversal pattern is a group of pages inspected by a user in a session. The other type of pattern may be uncovered by web usage mining. Patterns are found using different combinations which are used to discover different features and for different purposes.

Pattern analysis − When patterns are discovered, they must be analyzed to determine how that information can be used. Some of the patterns can be deleted and not determined to be of interest.

Pattern analysis is the phase of viewing and interpreting the outcomes of the discovery activities. It is not necessary to identify frequent types of traversal patterns, but also to identify patterns that are of interest because of their uniqueness or statistical properties.

Updated on 16-Feb-2022 05:52:19