Topic Tracker: By maintaining the user profile and based on the different topics explored by the user, the system predicts other topics of interest to the user. 5. Scientific advances: facilitate research based on concepts from biomedical literature and work on the hypothesis of the causes of rare diseases. Challenges in Text Mining The main challenge faced in Text Mining is the complexity arising from natural language itself. Natural language is not free from the problem of ambiguity; contains words that have the ability to be understood in two or more possible senses or ways. Ambiguity gives natural language its flexibility and usability; therefore it cannot be completely eliminated from natural language. • Semantic analysis methods used for text mining purposes are computationally expensive and operate on the order of a few words per second. This poses a challenge as to how semantic analysis can be made efficient and scalable for very large text corpora. • Multilingual text is another obstacle, text refinement algorithms are needed to refine multilingual text documents and produce language-independent intermediate forms. • Additionally, legal issues associated with copyright laws and database usage can hinder data extraction if owner permission is not obtained