A review of text mining approaches and their function in discovering and extracting a topic

Background and aim: Four text mining methods are examined and focused on understanding and identifying their properties and limitations in subject discovery. Methodology: The study is an analytical review of the literature of text mining and topic modeling.  Findings: LSA could be used to classify specific and unique topics in documents that address only a single topic. The other three text mining methods focus on topics and general partiality of the text. PLSA is applicable to documents dealing with a topic, unlike the LSA, it is used to discover general themes and contexts. However, LDA is more applicable to documents that address several issues. The CTM, method can be used to identify relationship between different subject categories. Conclusion: Text mining tactics are suitable for employing analysis in discovering and extracting the text subjects.