Intelligent Document Summarizer

ml, nlp, algorithms

A Document Summarizer is a tool which for a given input text file generates a output containing a list of sentences which better describes our original file. We began with eliminating unimportant words (such as stop words and punctuation ). We then calculate the term frequency of every important word ({words}\textbackslash{}{unimportant words}), and vectorize our sentences. We then cluster similar sentences together. In the process, we ignore the sentences which have nearly zero or near complete similarity. This is done to not let outliers affect our clustering. We then choose the sentences that describe the cluster best. An ordered collection of these sentences will be our summary of the input file

More information can be found here: