Hindi Text Summarizer
The system is based on a sentence scoring algorithm, supported by the emergence of subject-specific word numbering systems, that helps remove irrelevant phrases from the pre-selected resume suggestions, making the suggestions look more like human-generated resumes.
Abstract
: Text summarization involves reducing the text that is built from one or more texts so that particularly important information in the text is not lost. Text summarization compresses raw text to display only what is important and necessary for the user. When summarizing an article, decisions are often made quickly in order to capture the essence of the paper. It focuses on mining methods and applications in Python. The extraction method defines a set of sentences supported by the subject method. We also consider removing Hindi keywords and extracting nouns in sentences before selecting nouns. Disabling word removal removes empty keywords from input documents, and word search allows words to be grouped by matching numbering system terms. The system is based on a sentence scoring algorithm, supported by the emergence of subject-specific word numbering systems. The recommendations with the highest score will be added to the summary. The generated resumes are then processed to help remove irrelevant phrases from the pre-selected resume suggestions, making the suggestions look more like human-generated resumes.