[Purpose/significance] In the age of big data, information users are helpless when they face massive data. More and more scholars focus on the algorithm used to detect the hot topics of the Internet, helping information users get the hot topics quickly. [Method/process] Based on the DBSCAN, the improved algorithm can realize the goal of detecting the hot topics of the Internet by adjusting the parameters dynamically. The hot topic filtering model can filter the general topic of lexical to improve the accuracy of the results. [Result/conclusion] We use error rate and detection rate to prove the effectiveness of the algorithm. The experimental results of the improved algorithm show that the improved algorithm is more efficient than the original. In conclusion, the improved DBSCAN algorithm and the SDIRFM can offer efficient ways for information users to research network data.
Sun Mingxi
,
Liu Chunqi
. Research on Hot Topic Detection Based on DBSCAN Algorithm and Inter Sentence Relationship[J]. Library and Information Service, 2017
, 61(12)
: 113
-121
.
DOI: 10.13266/j.issn.0252-3116.2017.12.015
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