What method does the Bag-of-Words approach use to extract features from textual data?

What method does the Bag-of-Words approach use to extract features from textual data?

• A. Word definitions in a dictionary
• B. Word frequencies in a text
• C. Sentence structures
• D. Conceptual themes

Answer: (B)

The Bag-of-Words approach utilizes word frequencies in a text to extract features. This method represents text data by disregarding the order in which words appear and instead focuses solely on the counts of each word present. Each unique word in the document is treated as a feature in a high-dimensional space, and the frequency of each word contributes to the representation of the document. This means that if a word appears multiple times, its frequency will be recorded, which helps in tasks like text classification and sentiment analysis. This representation allows algorithms to effectively quantify the information derived from the text while simplifying the complexities associated with linguistic structures. Other options, while relevant to various aspects of text analysis, do not align with the core principle of the Bag-of-Words method, which specifically emphasizes word occurrences and their frequency as the primary basis for feature extraction.

The Bag-of-Words approach utilizes word frequencies in a text to extract features. This method represents text data by disregarding the order in which words appear and instead focuses solely on the counts of each word present. Each unique word in the document is treated as a feature in a high-dimensional space, and the frequency of each word contributes to the representation of the document.

This means that if a word appears multiple times, its frequency will be recorded, which helps in tasks like text classification and sentiment analysis. This representation allows algorithms to effectively quantify the information derived from the text while simplifying the complexities associated with linguistic structures.

Other options, while relevant to various aspects of text analysis, do not align with the core principle of the Bag-of-Words method, which specifically emphasizes word occurrences and their frequency as the primary basis for feature extraction.