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Query Specific Focused Summarization of Biomedical Journal Articles

Rai Akshara, Sangwan Suyash, Goel Tushar, Verma Ishan, Dey Lipika

Annals of Computer Science and Information Systems

2021

Vol. 25

91--100

During COVID-19, a large repository of relevant literature, termed as``CORD-19'', was released by Allen Instituteof AI. The repository being very large, and growing exponentially, concerned users are struggling to retrieve only required information from the documents. In this paper, we present a framework for generating focused summaries of journal articles. The summary is generated using a novel optimization mechanism to ensure that it definitely contains all essential scientific content. The parameters for summarization are drawn from the variables that are used for reporting scientific studies. We have evaluated our results on the CORD-19 dataset. The approach however is generic.

Survey of scientific document summarization methods

Kurian Sheena K., Mathew Sheena

Computer Science

2020

T. 21 (2)

141--177

The number of research papers published every year is growing at an exponential rate, which has led to intensive research in scientific document summarization. The different methods commonly used in automatic text summarization research are discussed in this paper, along with their pros and cons. Commonly used evaluation techniques and datasets in this field are also discussed. Rouge and Pyramid scores are tabulated for easy comparison of the results of various summarization methods.