Information Interactions: The Criteria of the Choice of Communication Channels in a Scientific and Technical Library

Paramonova, Irina

doi:10.3103/s0147688219030067

Cited by 2 publications

(1 citation statement)

References 1 publication

Supporting

Mentioning

Contrasting

Order By: Relevance

“…L&I information is commonly organized in two modes: information fusion and information aggregation [22,23]. Paramonova [24] enhanced the semantics of L&I information through information classification, ontology analysis, and data association method and relied on the semantics for knowledge organization and visual metering. In this way, knowledge organization was integrated with econometric analysis to mine the resource associations, through the analysis of cooccurrence relationships, coupling relationships, and social network analysis.…”

Section: Introductionmentioning

confidence: 99%

Information Visualization from the Perspective of Big Data Analysis and Fusion

Lin

2021

Scientific Programming

View full text Add to dashboard Cite

In the big data environment, the visualization technique has been increasingly adopted to mine the data on library and information (L&I), with the diversification of data sources and the growth of data volume. The previous research into the information association of L&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&I from the perspective of big data analysis and fusion. Firstly, the authors analyzed the topology of the L&I visualization network and calculated the metrics for the construction of L&I visualization topology map. Next, the importance of meta-paths of the L&I visualization network was calculated. Finally, a complex big data L&I visualization network was established, and the associations between information nodes were analyzed in detail. Experimental results verify the effectiveness of the proposed algorithm.

show abstract

Section: Introductionmentioning

confidence: 99%

Information Visualization from the Perspective of Big Data Analysis and Fusion

Lin

2021

Scientific Programming

View full text Add to dashboard Cite

show abstract

Information Visualization from the Perspective of Big Data Analysis and Fusion

Lin

2021

Wseas Transactions on Computers

View full text Add to dashboard Cite

In the big data environment, the visualization technique has been increasingly adopted to mine the data on library and information (L&I), with the diversification of data sources and the growth of data volume. However, there are several defects with the research on information association of L&I visualization network: the lack of optimization of network layout algorithms, and the absence of L&I information fusion and comparison in multiple disciplines, in the big data environment. To overcome these defects, this paper explores the visualization of L&I from the perspective of big data analysis and fusion. Firstly, the authors analyzed the topology of the L&I visualization network, and calculated the metrics for the construction of L&I visualization topology map. Next, the importance of meta-paths of the L&I visualization network was calculated. Finally, a complex big data L&I visualization network was established, and the associations between information nodes were analyzed in details. Experimental results verify the effectiveness of the proposed algorithm

show abstract

Information Interactions: The Criteria of the Choice of Communication Channels in a Scientific and Technical Library

Cited by 2 publications

References 1 publication

Information Visualization from the Perspective of Big Data Analysis and Fusion

Information Visualization from the Perspective of Big Data Analysis and Fusion

Information Visualization from the Perspective of Big Data Analysis and Fusion

Contact Info

Product

Resources

About