Query-based Abstractive Summarization Model Using Sentence Ranking Scores and Graph Techniques

Gihwan Kim, Youngjoong Ko

http://doi.org/10.5626/JOK.2020.47.12.1172

The purpose of the fundamental abstractive summarization model is to generate a short summary document that includes all important contents within the document. Conversely, in the query-based abstractive summarization model, information related to the query should be selected and summarized within the document. The existing query-based summarization models calculates the importance of sentences using only the weight of words through an attention mechanism between words in the document and the query. This method has a disadvantage in that it is difficult to reflect the entire context information of the document to generate an abstractive summary. In this paper, we resolve this problems by calculating the sentence ranking scores and a sentence-level graph structure. Our proposed model shows higher performance than the previous research model, 1.44%p in ROUGE-1 and 0.52%p in ROUGE-L.