Text Summarizer and Keyword Extractor

Project Code :TCMAPY975

Objective

The Machine Learning objective of a Text Summarizer and Keyword Extractor is to condense large amounts of text into concise summaries and identify key terms or phrases. This facilitates quick understanding of the content and Machine Learnings in information retrieval, making it useful for search optimization, content analysis, and efficient consumption of large textual datasets.

Abstract

The process of gaining and absorbing the knowledge from various sources is a time-consuming process where people, mainly youth spend time surfing over the internet for relevant information. The proposed system mainly focuses on scraping the data from websites and providing the summary as well as keywords from the information extracted from various websites giving the user flexibility to select the website of their choice. The proposed system for the text summarization and keyword extraction undergoes a sequence of steps starting from data extraction from a website link, removal of outliers and irrelevant information, emphasizing on the importance of particular data extracted from the website and creating a summary of the extracted data. For the selection of relevant information from the extracted data, it is necessary to use natural language processing. The proposed project helps its users to reduce their surfing time and gives summary prepared from multiple website links and documents or keywords from a particular website or a document.

Keywords: Summarization, multi-document summarization, keyword extraction, natural language processing, Text rank algorithm.

NOTE: Without the concern of our team, please don't submit to the college. This Abstract varies based on student requirements.