Research on Hot News Topic Detection of Incremental Clustering

doi:10.3969/j.issn.1006-2475.2017.03.010

Abstract

Abstract:

News text clustering is applied to achieve ranking and finding hot news topics. To obtain hot topic news ranking by the formula of heat, the reporting rate is studied.

To overcome the shortcomings of huge cost of calculation and inaccuracy of selecting eigenvalues when SinglePass is used to cluster, its proposed enhanced methods to solve

the problems. The improved algorithm is verified and analyzed through the experiment using fetched news corpus. The result of experiments is compared to the SinglePass, and a

more desirable hot news clustering effect is presented, the feasibility of modified algorithm is demonstrated.

Key words: hot news topic, text clustering, SinglePass algorithm, formula of heat

CLC Number:

TP393

WANG Liying1,2， GE Lina1,2， ZHANG Yipeng 1,2， WANG Hong1,2. Research on Hot News Topic Detection of Incremental Clustering[J]. Computer and Modernization, doi: 10.3969/j.issn.1006-2475.2017.03.010.

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