Final answer:
Optical Character Recognition (OCR) is the technology not primarily for extracting information from unstructured data sets; it digitizes text rather than analyzing or extracting meaning.
Step-by-step explanation:
The student's question pertains to the tools and technologies used for extracting information from unstructured data sets. Among the options provided:
- Natural Language Processing (NLP) is a subset of artificial intelligence (AI) that focuses on the interaction between computers and human language, particularly how to process and analyze large amounts of natural language data.
- Sentiment Analysis is a technique used to detect and extract subjective information in source material, which often involves understanding the sentiment expressed in text.
- Data Mining is the process of discovering patterns and knowledge from large amounts of data. The data source may be large databases, structured or unstructured.
- Optical Character Recognition (OCR) is the mechanical or electronic conversion of images of typed, handwritten, or printed text into machine-encoded text. While important for digitizing texts, it does not inherently extract meaning or patterns from data.
Considering these definitions, Optical Character Recognition (OCR) is the tool among the choices given which is not typically used for extracting information from unstructured data sets in the context of understanding their meaning or sentiment, but rather is used for the digitization of text.