• Shriganesh S. Lokapure
• Sourabh Mahajan
• Ameya Bhingarkar
• Sakshi Dhamne
• Shakeeb Sheikh

There is an enormous amount of textual information on the web and it is growing every single day. It is present in the form of web pages, blogs, articles, etc. and it needs to be structured so that it is easy for someone to get the context and the gist of the overall data in a concise form. It is a tedious task for humans to arrange the data manually and it also requires rigorous analysis of data. For that purpose, the data needs to be summarized. Nowadays, due to advancing technologies, understanding and interpreting concepts has become easier due to the visual representation of data. Concept maps are one of the ways to visually structure and represent data. Concept maps allow the users to group related information so that generation of a concept map becomes easier. This study proposes the method of a machine learning model for summarization and concept map generation without using the existing tools that are already present on the web. Various steps are performed to achieve the final output that is data summarization and concept map generation.

Concept map, Concept map mining, Text analysis, text summarization

"AUTOMATIC CONCEPT MAP GENERATION AND SUMMARIZATION FROM TEXT", International Journal of Emerging Technologies and Innovative Research (www.jetir.org), ISSN:2349-5162, Vol.8, Issue 5, page no.f104-f107, May-2021, Available :http://www.jetir.org/papers/JETIR2105676.pdf

"AUTOMATIC CONCEPT MAP GENERATION AND SUMMARIZATION FROM TEXT", International Journal of Emerging Technologies and Innovative Research (www.jetir.org | UGC and issn Approved), ISSN:2349-5162, Vol.8, Issue 5, page no. ppf104-f107, May-2021, Available at : http://www.jetir.org/papers/JETIR2105676.pdf