⊿ Point. {R} Glossary. ◢ Keyword: T. ▰ Sources. 〓 Books [B] ◥ University. {q} PhD. ⏫ THEMES. ⏫ Big Data. [B] Big Data. ⚫ USA. ↂ EndNote. ☢️ Operationalised. ☢️ Adv Analytics. ☝️ BD Dummies. Text mining. A typical application is to scan a set of documents written in a natural language and either model the document set for predictive classification purposes or populate a database or search index with the information extracted. Text mining and text analytics[edit] The term text analytics describes a set of linguistic, statistical, and machine learning techniques that model and structure the information content of textual sources for business intelligence, exploratory data analysis, research, or investigation.[1] The term is roughly synonymous with text mining; indeed, Ronen Feldman modified a 2000 description of "text mining"[2] in 2004 to describe "text analytics. "[3] The latter term is now used more frequently in business settings while "text mining" is used in some of the earliest application areas, dating to the 1980s,[4] notably life-sciences research and government intelligence.
History[edit] Text analysis processes[edit] Applications[edit] Security applications[edit] Software[edit]