Semantic Search and NLP-Based Diagnostics

This study considers issues in semantic representation of written texts, especially in the context of entropy-based approach to natural language processing in biomedical applications. These issues lie at the intersection of Web search methodologies, ontology studies, lexicon studies, and natural language processing. The presented in the article entropy-based methodology is aimed at enhancing search techniques and diagnostics by capturing semantic properties of written texts. The range of possible applications ranges from forensic linguistics to psychological diagnostics and evaluation. The presented case study assumes that for texts written under atypical mental conditions, the level of relative text entropy may fall below a certain threshold and the distribution of entropy across the text may show unusual patterns, thus contributing to the semantic assessment of a subject's mental state. Further processing methods potentially contributing to psychological evaluation diagnosis and ontology-based search are discussed.