Text Mining Techniques
QUESTION 1: What is the practical application of text mining?
Text mining can be applied in different ways. In this section, I will discuss 4 ways in which text mining is used.
A. Search Engines
Text mining can be used to create suggestions or recommendations based on user input; the Google search engine is a good example of this. As per Figure 1.1 below, if a person were to type the word ‘Education’ in the search engine, Google would retrieve results containing the word ‘Education’ in the first place (before retrieving results that are otherwise related to the word ‘Education’); the search engine would suggest pertinent pages with regards to the word ‘Education’.
Figure 1.1 | Searching the word ‘Education’ on Google (screenshot of results)
In Figure 1.1, we can see that the search engine uses text mining to find the searched word(s) and that it highlights the text matches in bold. Text mining is a powerful tool here as it helps millions of Internet users to find a variety of things through a simple keyboard input and a mouse click.
B. Customer Service and Email Support
“70% of an organization’s data is contained in free-text form” (Koslowsky, 2010); this means that there is a lot of benefits in digging data from written customer communications for a firm that’s deals directly with customers. Text mining allows businesses to notice the attitude of the customer in his/her written communications with the firm; whether the latter is angry, happy, on the verge of leaving the firm for competitors, etc. Text mining may be applied as a data extraction tool that would target those “pertinent words and phrases that identify the nature of the text” (Koslowsky, 2010). By analysing the actual words in a customer’s communication, a business can better cross-sell offerings; such usage of text mining allows businesses to be more sensitive to those customers that are prone to leave the firm for competitors and apply adequate solutions. As such, text mining is
Text mining can be applied in different ways. In this section, I will discuss 4 ways in which text mining is used.
A. Search Engines
Text mining can be used to create suggestions or recommendations based on user input; the Google search engine is a good example of this. As per Figure 1.1 below, if a person were to type the word ‘Education’ in the search engine, Google would retrieve results containing the word ‘Education’ in the first place (before retrieving results that are otherwise related to the word ‘Education’); the search engine would suggest pertinent pages with regards to the word ‘Education’.
Figure 1.1 | Searching the word ‘Education’ on Google (screenshot of results)
In Figure 1.1, we can see that the search engine uses text mining to find the searched word(s) and that it highlights the text matches in bold. Text mining is a powerful tool here as it helps millions of Internet users to find a variety of things through a simple keyboard input and a mouse click.
B. Customer Service and Email Support
“70% of an organization’s data is contained in free-text form” (Koslowsky, 2010); this means that there is a lot of benefits in digging data from written customer communications for a firm that’s deals directly with customers. Text mining allows businesses to notice the attitude of the customer in his/her written communications with the firm; whether the latter is angry, happy, on the verge of leaving the firm for competitors, etc. Text mining may be applied as a data extraction tool that would target those “pertinent words and phrases that identify the nature of the text” (Koslowsky, 2010). By analysing the actual words in a customer’s communication, a business can better cross-sell offerings; such usage of text mining allows businesses to be more sensitive to those customers that are prone to leave the firm for competitors and apply adequate solutions. As such, text mining is