In short, sample article is summarized using TF-IDF and Hopfield Network.
This project is divided into 3 parts:
Part 1: Finding TF-IDF score of each word
Part 2: Implementation of Hopfield Network to find the most important words
Part 3: Summarization by ranking each sentences based on Hopfield network outputs.
The sample article is taken from: https://www.theguardian.com/sport/2019/oct/12/eliud-kipchoge-makes-history-sub-two-hour-marathon
The whole project is an application based on:
Voronkov, I.M. and Kharlamov A.A. "Application of semantic networks in text classification tasks." In Proceedings of the 52nd scientific conference of MIPT "Modern problems of fundamental and applied sciences." Part I. Radio engineering and cybernetics. Volume 2. - M .: MIPT, Moscow, pp. 10-13. 2009.
(Применение семантических сетей в задачах классификации текстов И.М. Воронков, А.А.Харламов
Труды 52-й научной конференции МФТИ «Современные проблемы фундаментальных и прикладных наук».Часть I. Радиотехника и кибернетика.Том 2. — М.: МФТИ, 2009.)