Textual Data Structuring
M. Laeeq Khan · 2025
Abstract This chapter explores the different approaches of text analysis, text mining, and text analytics, which all refer to processes that assist in extracting meaning from textual data. The chapter highlights the significance of data structuring as a fundamental process, which can be regarded as an advanced form of data cleansing, processing, and organizing. The organization of information is vital for the efficient implementation of text analytics techniques. The key strategies discussed include text parsing and filtering; association, clustering, and classification; keyword identification and frequency analysis; text normalization; named entity recognition; and relationship extraction. The key process involves breaking down lengthier texts into smaller, more manageable units. These methods together allow for more precise and perceptive study of text, establishing the foundation for more extensive examination of textual data in different situations.