Abstractive Text Summarization on Google Search Results

This is the authors' abstract. We don't add key points for this paper.

The Internet has become the forefront of our lives, technological advancements help people in an efficient and better way. The capitalists, educators, analysts all share a lot of content on the web so that it becomes available to users and helps them to connect with people. However, there is an issue in presenting the data to the users so that they can get the best information with the least effort. The search engine only helps to filter out irrelevant documents, leaving difficult tasks such as reading and summarizing to ourselves.Our paper proposes a model that will set an interface for web scraping using Python, The SSN techniques will prepare an abstractive summary from the data appearing in the search result links. This will allow people to access the best information with minimal efforts. The time-consuming and tedious tasks such as retrieving and summarizing are left to the computers. For all the impatient users, who don’t have time to read the text carefully, such a system can be very useful to them.