K-means text clustering method and device of built-in constraint rules

The invention discloses a k-means text clustering method and device of built-in constraint rules. The method includes the steps of preprocessing a to-be-clustered text set through the second constraint rule to obtain a second preprocessing set corresponding to the second constraint rule, obtaining k...

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Bibliographic Details
Main Authors JIN YAOHONG, XI LINA, LI DEYAN
Format Patent
LanguageChinese
English
Published 20.04.2018
Subjects
CALCULATING
COMPUTING
COUNTING
ELECTRIC DIGITAL DATA PROCESSING
HANDLING RECORD CARRIERS
PHYSICS
PRESENTATION OF DATA
RECOGNITION OF DATA
RECORD CARRIERS
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Summary:The invention discloses a k-means text clustering method and device of built-in constraint rules. The method includes the steps of preprocessing a to-be-clustered text set through the second constraint rule to obtain a second preprocessing set corresponding to the second constraint rule, obtaining k texts in the to-be-clustered text set to serve as the cluster center, if the cluster center is contained in one sub-set of the second preprocessing set, adding texts in another sub-set of the second preprocessing set into a cluster exclusive set corresponding to the cluster center, if current textsin the to-be-clustered text set are contained in x cluster exclusive sets, calculating the distances between other (k-x) cluster centers except the cluster center corresponding to the cluster exclusive set and the current texts, adding the current texts into the cluster corresponding to the cluster center nearest to the current texts, recalculating a new cluster center of each cluster, and if thenew cluster centers meet
Bibliography:Application Number: CN201711236589