Hybrid methodologies for summarisation of Kannada language text documents. Issue 1 (9th December 2014) - Jayashree, R.; Murthy, K. Srikanta; Anami, Basavaraj S.
The problem of information explosion is becoming a serious concern. In this regard, any new methodology developed to solve the issues related to information retrieval (a.k.a. Information Retrieval or IR) draws wide attention. Text summarisation is a predominant field of NLP which may provide promising solution to the issues stated earlier. Text summarisation or text document summarisation provides a quick and concise meaning of the document without even reading the whole document. In this work, we have developed hybrid methodologies for providing summary of a given document in the Kannada language. The approach is new as we have used combination of feature selection methods as a pre–processing step for summarisation. In this work, we have devised four different methodologies for text document summarisation, which focus on text extraction, which is an open approach as stated earlier: (a) summarisation based on keywords, (b) summarisation based on sentence ranking, (c) summarisation based on Jaccards' similarity score and (d) summarisation based on neural network approach.