arXiv Open Access 2022

COV19IR : COVID-19 Domain Literature Information Retrieval

Arusarka Bose Zili Zhou Guandong Xu

Lihat Sumber

Abstrak

Increasing number of COVID-19 research literatures cause new challenges in effective literature screening and COVID-19 domain knowledge aware Information Retrieval. To tackle the challenges, we demonstrate two tasks along withsolutions, COVID-19 literature retrieval, and question answering. COVID-19 literature retrieval task screens matching COVID-19 literature documents for textual user query, and COVID-19 question answering task predicts proper text fragments from text corpus as the answer of specific COVID-19 related questions. Based on transformer neural network, we provided solutions to implement the tasks on CORD-19 dataset, we display some examples to show the effectiveness of our proposed solutions.

Topik & Kata Kunci

cs.IR cs.CL

Penulis (3)

Arusarka Bose

Zili Zhou

Guandong Xu

Format Sitasi

APA MLA BibTeX

Bose, A., Zhou, Z., Xu, G. (2022). COV19IR : COVID-19 Domain Literature Information Retrieval. https://arxiv.org/abs/2211.04013

Akses Cepat

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Informasi Jurnal

Tahun Terbit: 2022
Bahasa: en
Sumber Database: arXiv
Akses: Open Access ✓