With the advent of the age of information technology, we have entered the sea of information. This information explosion is based on the Internet; it has become one of the general infrastructures of information. We cannot deny the fact that the content of information based on the Internet is growing rapidly every day, so it is increasingly difficult to obtain the information we really want. Web mining is a tool that can be used to customize websites based on their content and based on user interface. Web mining usually includes usage mining, content mining and structure mining.
Data mining, text mining, and web mining use various technologies and procedures to extract appropriate information from a huge database; therefore, companies can make better business decisions accurately. Therefore, data mining, text mining, and web mining are promoting ” The goal of “customer relationship management” is very helpful; its main goal is to initiate, expand and personalize customer relationships by profiling and classifying customers.
However, when dealing with the Web mining process, many problems must be solved. Data privacy can be said to be the issue of the trigger button. Recently, as traders, companies, and governments continue to collect and store large amounts of private information, complaints and concerns about privacy violations have greatly escalated. People are not only concerned with the collection and compilation of private information, but also with the analysis and use of such data. Driven by the growing public interest in synthetic statistics and the number of available technologies; in the next few years, conflicts between data privacy and mining may lead to higher levels of inspection. Legal conflicts are also likely to occur in this regard.
Data mining also faces other problems. “Incorrect information” may cause us to carry out ambiguous analysis and incorrect results and suggestions. The wrong data or wrong information submitted by customers during the data import process will bring real harm to the efficiency and effectiveness of Web Mining. Another risk of data mining is that mining may be confused with data warehouses. Companies that develop information warehouses without the use of appropriate mining software are unlikely to achieve levels of accuracy and efficiency, and are unlikely to receive full benefits from there. Similarly, if cross-selling will destroy customers ’privacy, destroy their beliefs, or annoy them with unnecessary demands, it may cause difficulties. Network mining can greatly help improve and arrange marketing plans that target customers’ interests and needs.
Despite potential obstacles and barriers, the Web mining market is expected to grow by billions of dollars in the next few years. Mining helps to identify and locate potential customers whose information is “hidden” in massive databases and enhances customer relationships. Data mining tools can predict future market trends and consumer behavior, which may help companies adopt proactive, knowledge-based solutions. This is one of the reasons why data mining is also called “knowledge discovery”. It can be said that this is the process of analyzing the data from different angles, classifying and grouping the identified data, and finally building a useful information database. The company can further analyze and use it to increase and generate revenue and reduce costs. By using data mining, business organizations find that it is easier to answer queries related to business capabilities and intelligence, which are very complex and require earlier analysis and determination.