Paper Title
Implementation of Automated Text Summary using Minimum Dominating Set

The idea is to use concept of Minimum Dominating Set in Graph Theory to develop a technique for text summarization of a document. For this we use the learning procedure of Word Embeddings that maps words and expressions in a text document to vectors of real numbers which helps the algorithm to learn similarity between the words. Then the sentences are vectorized as a whole to give us a weighted complete graph showcasing degree of relation between each sentence. The Minimum Dominating Set of this weighted complete graph gives us the final text summary. This technique is then compared with other existing techniques used by online text summarization websites to conclude its superiority over their techniques. Keywords - Minimum Dominating Set, Word Embedding, GloVe, Text Summarization, Graph Theory