Text Mining is also known as Text Analytics. It is the process of understanding information from a set of texts. It is designed to help the business find out valuable knowledge from text based content. These contents can be in the form of word document, email or postings on social media. It use of automated methods for understanding the knowledge available in the text documents.
Text Mining can also be used to make the computer understand structured or unstructured data. Qualitative data or unstructured data are data that cannot be measured in terms of numbers. These data usually contain information like colour, texture and text. Quantitative data or structured data are data that can be measured easily.
Text mining is an interdisciplinary field which includes information retrieval, data mining, machine learning, statistics and others.
Advantages of Text Mining
There are a lot of advantages of using Text Mining. They are listed below
- It saves time and resources and performs efficiently than human brains.
- It helps to track opinions over time
- It helps to summarize the documents
- Text analytics helps to extract concepts from text and present it in a more simple way
- The text which is indexed using Text mining can be used in predictive analytics
- You can plug in any vocabularies to use the terminology in your area of interest
Applications of Text Mining
The technology is now broadly applied for a wide variety of government, research, and business needs. Applications can be sorted into a number of categories by analysis type or by business function. Using this approach to classifying solutions, application categories include:
- Enterprise Business Intelligence/Data Mining, Competitive Intelligence
- E-Discovery, Records Management
- National Security/Intelligence
- Scientific discovery, especially Life Sciences
- Sentiment Analysis Tools, Listening Platforms
- Natural Language/Semantic Toolkit or Service
- Automated ad placement
- Search/Information Access
- Social media monitoring