Odia Text Summarization Using Stemmer

Abstract

Lot of work has already been done for automatic text summarization. In this paper we have given a novel statistical approach to summarize the given Odia text. In our approach extraction of relevant sentences is done which can give the actual concept of the input document in a concise form. We rank each sentence in the document by assigning a weight value to each word of the sentence. The sentences are extracted as per their rank, which will lead to a good summary of the given text.

Extractive Odia Text Summarization System: An OCR Based Approach

“…al. has done the summarization by using an Odia stemmer [3]. In their work they take a part of the text as for their implementation, first, they had tokenized the whole text and in the second step, they remove the stop words.…”

A Simple and Efficient Text Summarization Model for Odia Text Documents

“…Similarly considering applicability of clustering one of the method used by the proposed model, has always been effective in removing redundancy [Oufaida et al (2014) Considering Odia language, limited research on the discussed topic has been reported. A summarizer [Balabantaray et al (2012)] based on normalized frequency count of the content words (exclusive of stop words) for determining significant sentences has claimed an average accuracy of 61%. The first sentence of the document has been mandatorily included in the summary giving importance to sentence position in the input document and compression ratio is kept at 50%.…”

A Survey of Text Summarization Techniques for Indian Regional Languages

“…R.C.Balabantaray have worked on Odia text summarization using stemmer. A novel statistical approach has been applied to summarize the given Odia text [19].…”