In AI systems, learning and understanding a topic requires processing vast amounts of information from sources such as books, articles, and magazines. What is this collection of textual data commonly called? Get a comprehensive answer and detailed explanation based on IBM Artificial Intelligence Fundamentals certification requirements.
Table of Contents
Question
In AI systems, learning and understanding a topic requires processing vast amounts of information from sources such as books, articles, and magazines. What is this collection of textual data commonly called?
A. Corpus
B. Vectorized text
C. Decoded contextual information
D. Encoded contextual information
Answer
A. Corpus
Explanation
The collection of textual data—comprising books, articles, magazines, and similar materials—used by AI systems to learn and process information is called a corpus.
A corpus (plural: corpora) refers to a large and structured set of texts or data intentionally collected and used for research, training, and language processing by AI and machine learning systems. These corpora are foundational in fields like natural language processing (NLP) and are often made up of diverse sources including books, articles, web pages, and transcripts.
In the context of AI, a corpus provides the substantial amount of raw data necessary for understanding language, context, and meaning, enabling accurate modeling and information extraction.
Terms like “vectorized text,” “decoded contextual information,” and “encoded contextual information” refer to particular processing stages or representations of data, not the original, holistic dataset.
This terminology and concept are central to success on the IBM Artificial Intelligence Fundamentals certification exam.
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