Text Segmentation - Approaches, Datasets, and Evaluation Metrics

Text segmentation is the process of dividing text into meaningful segments, such as words, sentences, or topics. One specific type of text segmentation task is topic segmentation, which divides a long body of text into segments that correspond to distinct topics or subtopics. Topic segmentation can improve readability and make downstream tasks like summarization or information retrieval easier. Common evaluation metrics for topic segmentation models include precision & recall, Pk, and WindowDiff. Both supervised and unsupervised methods can be used to train text segmentation models, depending on the specific task at hand.