Abstract—Automatic text summarization is technique of compressing the original text into shorter form which will provide same meaning and information as provided by original text. The brief summary produced by summarization system allows readers to quickly and easily understand the content of original documents without having to read each individual document. The overall motive of text summarization is to convey the meaning of text by using less number of words and sentences. Summaries are of two types: Abstractive summaries and Extractive summaries. Extractive summaries involve extracting relevant sentences from the source text in proper order. The relevant sentences are extracted by applying statistical and language dependent features to the input text. On the other hand, abstractive text summaries are made by applying natural language understanding. Human beings usually make summaries in abstractive way. Moreover abstractive summaries can also involve the words or sentences which are not present in the input text. Automatic generation of abstractive summary is more difficult as compared to producing extractive text summary. This paper concentrates on survey and performance analysis of automatic text summarizers for Indian languages.

Index Terms—indian summarizers, summarizers, text summarization system

Cite: Vishal Gupta, "A Survey of Text Summarizers for Indian Languages and Comparison of their Performance," Journal of Emerging Technologies in Web Intelligence, Vol. 5, No. 4, pp. 361-366, November 2013. doi:10.4304/jetwi.5.4.361-366