Difference between Data mining and Text mining
Data mining can be understood as a process of data extraction from a huge data set. The data is extracted to acquire knowledge about certain data sets to be further used for learning and processing purposes.
Data mining involves the following steps:
Applications of Data Mining
Market analysis is one such application of data science that helps analyze the current status of the market. As a result, it enables an individual in decision-making in terms of investments and business strategies for generating profit.
Frauds can be easily detected with the help of fraud detection by extracting more and more information related to any particular instance and then formulating a decision whether it is legal or illegal.
It extracts customer's information based on their interests and offers them exciting deals to buy any particular product. These strategies not only help in providing a high level of customer satisfaction but also maintain a healthy relationship with them.
With the help of data mining, we can extract previous experiments or test case's knowledge and further utilize it to work proficiently. In this way, the errors can be minimized by learning from preceding mistakes and utilized for producing better results.
Text Mining is also known as text data mining. It refers to the process of extracting high-quality data from the text. High-quality data is usually extracted through the discovering of patterns and trends such as statistical pattern learning.
Text analysis includes pattern recognition, information extraction, information retrieval, data mining techniques involve association analysis, visualization, and predictive analytics.
Text Mining comprises a wide range of methods; the primary three methods are given below.
In keyword-based technologies, the input is based on the keywords selected in the text extracted as a series of character strings.
Statistics technologies refer to the system which is based on machine learning. It has a training set of documents used as a model to categorize and manage text.
Linguistic based technologies
Linguistic-based technologies are a method based on a language processing system. The output f the text analysis gives an understanding of the structure of the text, logic, and grammar employed.
Application of Text Mining
Risk management is the process of identifying risk, quantifying that risk, and then employing different types of strategies to manage that risk. Preliminary risk analysis is usually a primary cause of failure of any industry. Primarily in the financial industry, where adoption of risk management software based on text mining can enhance the capability to reduce risk.
Customer care services
Customer service is the act of taking care of the customer's needs by providing and delivering professional, helpful, high-quality service and assistance before, during, and after the customer's requirements are met. Nowadays, text analytics software is adopted to enhance customer experience using various sources of information such as trouble tickets, surveys, and reviews to improve the management, quality, and speed in resolving problems.
Difference between Data Mining and Text Mining