J.B. Hunt Business
Link to the article:
https://www.ibm.com/docs/en/spss-modeler/SaaS?topic=help-about-spss-modeler-text-analytics
To handle a wide range of unstructured text data in a short amount of time, IBM's SPSS Modeler Text Analytics, which possesses powerful text analytic capabilities and makes use of advanced linguistic technologies and Natural Language Processing, is utilized (IBM, n.d.). The SPSS Modeler Text Analytics software from IBM can navigate the amazing amount of information on the globe in a rapid and effective manner (IBM, n.d.). Creating predictive analytics, data visualization, and machine learning are all made easier with its assistance. IBM, which is the world's largest provider of data storage and retrieval services, is required to continually test and utilize its own products and services to provide the best possible experience for its clients. Text data mining is a method that IBM utilizes to find relevant patterns and fresh insights. This process involves translating unstructured text into a structured format (IBM, n.d.). Companies can investigate and uncover previously unknown links within their unstructured data by utilizing sophisticated analytical methods such as Support Vector Machines and other deep learning algorithms (IBM, n.d.). Since text is one of the most common forms of data in databases, it may be arranged in three distinct ways, namely structured data, unstructured data, and semi-structured
data, depending on the database. Text mining techniques include information retrieval, natural language processing, and information extraction. These are some of the most frequent approaches.
References:
Jaggia, S. (2023).
Business analytics: Communicating with numbers
(2nd ed.). McGraw-Hill Higher Education.
