The scenario describes an application that must understand and process human language—specifically, written customer feedback—to classify it into predefined categories. This task of enabling computers to process, analyze, and derive meaning from textual data is the core function of Natural Language Processing (NLP). Text classification, as described in the question, is a fundamental and widely used NLP technique.

1. Jurafsky

D.

& Martin

J. H. (2023). Speech and Language Processing (3rd ed. draft). In Chapter 4

"Naive Bayes

Text Classification

and Sentiment

" the authors introduce text classification as a primary task of NLP: "The task of text classification is to take a text... and assign it a class... from a fixed set of classes." The scenario of classifying feedback into categories like "product quality" is a direct example of this.

2. Amazon Web Services (AWS). (n.d.). What is Natural Language Processing (NLP)? AWS documentation defines NLP as a field of AI that "focuses on enabling computers to understand

interpret

and manipulate human language." It lists text classification and sentiment analysis (a related task) as key applications.

3. Manning

C. D. (2011). CS224N: Natural Language Processing with Deep Learning

Lecture 1: Introduction and Word Vectors. Stanford University. The introductory lecture defines NLP as the field that gives "machines the ability to read

understand and derive meaning from human languages." The task of classifying customer feedback fits squarely within this definition.

4. Aggarwal

C. C.

& Zhai

C. (2012). A Survey of Text Classification Algorithms. In C. C. Aggarwal & C. Zhai (Eds.)

Mining Text Data (pp. 163-222). Springer. Section 1.1

"Introduction

" describes text classification as "the problem of assigning a document to one or more predefined categories

" which directly aligns with the scenario presented in the question. DOI: https://doi.org/10.1007/978-1-4614-3223-46