• Naga Sudha
• Y.Madhavee Latha

Automatic text summarization is a technique which compresses large text into a shorter text which includes the important information. Telugu is the most popular language used in south India and there is a lack of proper summarization system for telugu text. Hence,in this paper, we present an approach to the design an automatic text summarizer for telugu text that generates a summary by extracting sentences. It deals with a single document summarization based on feature weighting approach. Each sentence in the document is represented by a set of various features namely- key phrase ,sentence paragraph position, sentence overall position, numeric data, presence of inverted commas, sentence length and keywords in sentences. The sentence score is calculated and based on their score is used based on the feature vector. Then based on the required compression ratio, sentences are included in the final summary. The experiment was performed on news articles of different category such as education,Technology, movies, business and sports. The performance of the technique is then compared with the human generated summaries.

Text detection, character recognition, text extraction, scene image,text alignment,stroke width transform.

"Document Summarization for Telugu News Articles", International Journal of Emerging Technologies and Innovative Research (www.jetir.org), ISSN:2349-5162, Vol.6, Issue 5, page no.8-15, May-2019, Available :http://www.jetir.org/papers/JETIR1905Q02.pdf

"Document Summarization for Telugu News Articles", International Journal of Emerging Technologies and Innovative Research (www.jetir.org | UGC and issn Approved), ISSN:2349-5162, Vol.6, Issue 5, page no. pp8-15, May-2019, Available at : http://www.jetir.org/papers/JETIR1905Q02.pdf