Web Mining | Meaning and Purpose
With the bang of the era of information technology, we have entered into an ocean of information. This information blast is firmly based on the internet; which has become one of the universal infrastructures of information. We can not deny the fact that, with every passing day, the web-based information contents are increasing by leaps and bounds and as such, it is becoming more and more difficult to get the desired information which we are looking for. Web mining is a tool, which can be used in customising the websites from its contents and also from the user interface. Web mining comprises typically of usage mining, content mining and structure mining.
Data mining, text mining and web mining, engages various techniques and procedures to take out appropriate information from the vast database; so that companies can take better business decisions with precision. Hence, data mining, text mining and web mining help a lot in the promotion of the ‘customer relationship management’ goals; whose primary objective is to kick off, expand, and personalise a customer relationship by profiling and categorising customers.
However, there are numbers of matters that must be addressed while dealing with the process of web mining. Data privacy can be said to be the trigger-button issue. Recently, privacy violation complaints and concerns have escalated significantly, as traders, companies, and governments continue to gather and warehouse massive amount of private information. There are concerns, not only about the collection and compilation of private information but also the analysis and use of such data. Fueled by the public’s concern about the increasing volume of composed statistics and useful technologies; conflict between data privacy and mining is likely to root higher levels of inspection in the coming years. Legal conflicts are also pretty likely in this regard.
There are also other issues facing data mining. ‘Erroneousness of Information’ can lead us to vague analysis and incorrect results and recommendations. Customers’ submission of incorrect data or false information during the data importation procedure creates a real hazard for the web mining’s efficiency and effectiveness. Another risk in data mining is that the mining might get confused with data warehousing. Companies generating information warehouses without employing the proper mining software are less likely to reach the level of accuracy and efficiency, and also they are less likely to receive the full benefit from there. Likewise, cross-selling may pose difficulty if it breaks the customers’ privacy, breach their faith or annoys them with additional solicitations. Web mining can be of great help to improve and line-up the marketing programs, which targets customers’ interests and needs.
In spite of potential hurdles and impediments, the market for web mining is predicted to grow by several billion dollars in the coming years. Mining helps to identify and target the potential customers, whose information are “buried” in massive databases and to strengthen the customer relationships. Data mining tools can predict the future market trends and consumer behaviours, which can potentially help businesses to take proactive and knowledge-based resolutions. This is one of the causes why data mining is also termed as ‘Knowledge Discovery’. It can be said to be the process of analysing data from different points of view and sorting and grouping the identified data and finally to set up a useful information database, which can further be analysed and exploited by companies to increase and generate revenue and cut costs. With the use of data mining, business organisations are finding it more comfortable to answer queries relating to business aptitude and intelligence, which were very much complicated and intricate to analyse and determine earlier.