The automatic creation of concept maps from documents written using morphologically rich languages

Concept map is a graphical tool for representing knowledge. They have been used in many different areas, including education, knowledge management, business and intelligence. Constructing of concept maps manually can be a complex task; an unskilled person may encounter difficulties in determining and positioning concepts relevant to the problem area. An application that recommends concept candidates and their position in a concept map can significantly help the user in that situation. This paper gives an overview of different approaches to automatic and semi-automatic creation of concept maps from textual and non-textual sources. The concept map mining process is defined, and one method suitable for the creation of concept maps from unstructured textual sources in highly inflected languages such as the Croatian language is described in detail. Proposed method uses statistical and data mining techniques enriched with linguistic tools. With minor adjustments, that method can also be used for concept map mining from textual sources in other morphologically rich languages.

► A concept map mining process is defined. ► Overview of different approaches to automatic creation of concept maps is given. ► One method for creation of concept maps from unstructured text is proposed. ► Method uses statistical and data mining techniques enriched with linguistic tools. ► It is suitable for the creation of concept maps in highly inflected languages.