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Research on the Algorithms and Visualization Analysis Tool of the Burst Detection Analysis Method Based on Multiple Relationships in Collections of Journal Papers
Received date: 2015-11-06
Revised date: 2015-12-07
Online published: 2015-12-20
[Purpose/significance] The burst detection analysis method based on multiple relationships in collections of journal papers is a knowledge discovery method for multiple co-occurrences and hot topics in scientific and technicalpapers. It is significant to detect the research content and predict the research trends in papers' data stream.[Method/process] This paper focused on the burst detection problem of multiple co-occurrences in collections of journal papers. By comparing the algorithms of burst detection, the author selected a suitable algorithm in this research and developed the visualization analysis tool and designs the analysis model for burst detection analysis on multiple co-occurrences. This paper further applied the multiple co-occurrences burst detection method to reveal the research trends and hot topics in a set of institutes' papers.[Result/conclusion] By applying this method to the annual published papers' detection of scientific research institutions, we can analyze the burst detection situation of authors, key words, published journals and their relationships (such as the authors-keywords, etc.). We can also dig out deeper information contents than the general burst detection analysis method.
Pang Hongshen . Research on the Algorithms and Visualization Analysis Tool of the Burst Detection Analysis Method Based on Multiple Relationships in Collections of Journal Papers[J]. Library and Information Service, 2015 , 59(24) : 115 -122 . DOI: 10.13266/j.issn.0252-3116.2015.24.017
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