[Purpose/significance] In order to solve the problem of topic selection for professional fields in publishing industry, this paper integrates multisource dynamic information on the Internet to detect the hotspots for professional fields through multi-dimensional intelligence analysis. The data-driven topic selection is realized to lay a solid foundation for the digitization transformation and development of publishing industry.[Method/process] A intelligence analysis model towards topic selection was proposed to detect hotspots in professional fields. The model was divided into two steps:the hotspot discovery and the hotness evaluation. The hotspot discovery in this model identified hotspots in professional fields through word frequency statistics and the algorithm of word growth rate. Then, in the step of hotness evaluation, a series of indices in the dimension of content and spread were designed to calculate and evaluate the hotness of the hotspots identified in the last step.[Result/conclusion] A hotspots detecting experiment was conducted with 36,550 pieces of Chinese multisource dynamic information in the area of ICT collected from January to April of 2018, which verified the effectiveness of the proposed model. This model can be used in publishing industry to complete the step of topic selection scientificallyn
Wang Xiaoguang
,
Wang Hongyu
,
Huang Han
. Towards Professional Publishing: Research on Hotspot Detection Model Based on Multi-source Data[J]. Library and Information Service, 2019
, 63(14)
: 52
-61
.
DOI: 10.13266/j.issn.0252-3116.2019.14.007
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