{"status":"ok","message-type":"work","message-version":"1.0.0","message":{"indexed":{"date-parts":[[2025,5,14]],"date-time":"2025-05-14T02:45:06Z","timestamp":1747190706866,"version":"3.40.5"},"reference-count":27,"publisher":"Wiley","license":[{"start":{"date-parts":[[2021,11,8]],"date-time":"2021-11-08T00:00:00Z","timestamp":1636329600000},"content-version":"unspecified","delay-in-days":0,"URL":"https:\/\/creativecommons.org\/licenses\/by\/4.0\/"}],"content-domain":{"domain":[],"crossmark-restriction":false},"short-container-title":["Scientific Programming"],"published-print":{"date-parts":[[2021,11,8]]},"abstract":"<jats:p>In the big data environment, the visualization technique has been increasingly adopted to mine the data on library and information (L&amp;I), with the diversification of data sources and the growth of data volume. The previous research into the information association of L&amp;I visualization network rarely tries to construct such a network or explore the information association of the network. To overcome these defects, this paper explores the visualization of L&amp;I from the perspective of big data analysis and fusion. Firstly, the authors analyzed the topology of the L&amp;I visualization network and calculated the metrics for the construction of L&amp;I visualization topology map. Next, the importance of meta-paths of the L&amp;I visualization network was calculated. Finally, a complex big data L&amp;I visualization network was established, and the associations between information nodes were analyzed in detail. Experimental results verify the effectiveness of the proposed algorithm.<\/jats:p>","DOI":"10.1155\/2021\/8934632","type":"journal-article","created":{"date-parts":[[2021,11,8]],"date-time":"2021-11-08T23:50:06Z","timestamp":1636415406000},"page":"1-12","source":"Crossref","is-referenced-by-count":1,"title":["Information Visualization from the Perspective of Big Data Analysis and Fusion"],"prefix":"10.1155","volume":"2021","author":[{"ORCID":"https:\/\/orcid.org\/0000-0003-3883-6519","authenticated-orcid":true,"given":"Xiang","family":"Lin","sequence":"first","affiliation":[{"name":"Research Center for Advertising and Media Economics, Wuhan Technology and Business University, Wuhan 430065, China"}],"role":[{"role":"author","vocabulary":"crossref"}]}],"member":"311","reference":[{"key":"1","doi-asserted-by":"publisher","DOI":"10.1108\/vjikms-11-2018-0098"},{"key":"2","doi-asserted-by":"publisher","DOI":"10.1109\/icpc.2019.00053"},{"key":"3","doi-asserted-by":"publisher","DOI":"10.1109\/jcdl.2019.00030"},{"key":"4","doi-asserted-by":"publisher","DOI":"10.1007\/978-3-030-30763-9_8"},{"key":"5","doi-asserted-by":"publisher","DOI":"10.3233\/efi-190248"},{"key":"6","doi-asserted-by":"publisher","DOI":"10.1080\/0194262x.2018.1456391"},{"key":"7","doi-asserted-by":"publisher","DOI":"10.18280\/ts.370314"},{"key":"8","doi-asserted-by":"publisher","DOI":"10.18280\/i2m.180507"},{"issue":"3","key":"9","doi-asserted-by":"crossref","first-page":"209","DOI":"10.18280\/ts.360302","article-title":"Design and application of an adaptive slow feature extraction algorithm for natural images based on visual invariance","volume":"36","author":"Y. 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