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An Intelligent Retrieval Algorithm for Digital Literature Promotion Information Based on TRS Information Retrieval

An Intelligent Retrieval Algorithm for Digital Literature Promotion Information Based on TRS Information Retrieval

Tong Ni
Copyright: © 2023 |Volume: 16 |Issue: 2 |Pages: 14
ISSN: 1935-570X|EISSN: 1935-5718|EISBN13: 9781668488676|DOI: 10.4018/ijitsa.318458
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MLA

Ni, Tong. "An Intelligent Retrieval Algorithm for Digital Literature Promotion Information Based on TRS Information Retrieval." IJITSA vol.16, no.2 2023: pp.1-14. http://doi.org/10.4018/ijitsa.318458

APA

Ni, T. (2023). An Intelligent Retrieval Algorithm for Digital Literature Promotion Information Based on TRS Information Retrieval. International Journal of Information Technologies and Systems Approach (IJITSA), 16(2), 1-14. http://doi.org/10.4018/ijitsa.318458

Chicago

Ni, Tong. "An Intelligent Retrieval Algorithm for Digital Literature Promotion Information Based on TRS Information Retrieval," International Journal of Information Technologies and Systems Approach (IJITSA) 16, no.2: 1-14. http://doi.org/10.4018/ijitsa.318458

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Abstract

The world has entered the information age, and one of the main factors of social development is various information resources. Word processing is one of the first information technologies to be developed that has grown very rapidly and successfully. As a category of multimedia resources, documents are widely used in institutions, such as corporations, governments, and digital libraries. Traditional search technology has been unable to meet the needs of this development, and how to find information in this sea of digital information has become an urgent problem. Therefore, this study has conducted a research experiment on promoting digital literature for text retrieval system information retrieval. The experimental data have shown that 310 (73.81%) students wanted WeChat and Weibo as a way of digital literature retrieval and promotion. Moreover, 267 (63.57%) students wanted e-books as a way to promote, and 172 (40.95%) students would like to participate in novel digital literature retrieval promotion activities.