Seed-guided topic model for document filtering and classification

• Main Authors: Li, Chenliang, Chen, Shiqian, Xing, Jian, Sun, Aixin, Ma, Zongyang
• Other Authors: School of Computer Science and Engineering
• Format: Article
• Language: English
• Published: 2020
• Subjects: Engineering::Computer science and engineering; Topic Model; Dataless Classification
• Online Access: https://hdl.handle.net/10356/142845
• Institution: Nanyang Technological University

One important necessity is to filter out the irrelevant information and organize the relevant information into meaningful categories. However, developing text classifiers often requires a large number of labeled documents as training examples. Manually labeling documents is costly and time-consuming...