TF-IDF and Key Phrase Identification Based Malayalam Document Summarization

Abstract

The purpose of text summarization is to condense long pieces of text into more manageable chunks. The objective is to create a syntactically sound and grammatically clear summary of the document's key points. Natural language processing (NLP) includes this crucial task, which unquestionably affects the synthesization of processes undertaken. Because of time limits and the proliferation of available information in digital form, it is no longer feasible to carefully read an article, record, or book to decide its relevance. When it comes to machine learning and natural language processing, automatically summarising texts is a common challenge. This study contrasts the results of Malayalam text summarization using the Term Frequency - Inverse Document Frequency (TF-IDF) algorithm with those obtained using the Key Phrase Made it official.