A Study on Ontology Based Abstractive Summarization

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With widespread use of Internet and the emergence of information aggregation on a large scale, a quality text summarization is essential to effectively condense the information. Automatic summarization systems condense the documents by extracting the most relevant facts. Summarization is commonly classified into two types, extractive and abstractive. Summarization by abstraction needs understanding of the original text and then generating the summary which is semantically related. Abstractive summarization requires the understanding of complex natural language processing tasks. There are many methods adopted for abstractive summarization. Ontology is one among the approach used for getting abstractive summary for a specific domain. In this paper, we discuss about various works carried out using ontology for abstractive text summarization.

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Jishma Mohan, M., Sunitha, C., Ganesh, A., & Jaya, A. (2016). A Study on Ontology Based Abstractive Summarization. In Procedia Computer Science (Vol. 87, pp. 32–37). Elsevier B.V. https://doi.org/10.1016/j.procs.2016.05.122

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