Incremental clustering method and device based on human-computer interaction, equipment and storage medium

A technology of incremental clustering and human-computer interaction, applied in the field of big data processing, to achieve the effect of improving the recall rate of clustering, ensuring the accuracy of clustering, and solving how to deal with it effectively.

CN113936160APending Publication Date: 2022-01-14恒睿(重庆)人工智能技术研究院有限公司
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Authority / Receiving Office
CN · China
Current Assignee / Owner
Publication Date
2022-01-14

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Abstract

The invention belongs to the technical field of big data processing, particularly provides an incremental clustering method and device based on human-computer interaction, equipment and a storage medium, and aims to solve the problem of how to process suspected merging result pairs in incremental clustering results. In order to achieve the purpose, the method comprises the steps of obtaining newly-added data and first clustering data, wherein the first clustering data are historical data subjected to clustering; performing incremental clustering to obtain second clustering data and / or suspected merged data; according to a result of priority ranking of suspected merged data pairs in the suspected merged data, manually intervening and processing the suspected merged data pairs to obtain third clustering data; and updating the first clustering data according to the second clustering data and the third clustering data. By applying the method provided by the invention, whether the suspected merged data pair needs to be merged or not is manually judged, so that the merging of clustering errors is inhibited, the correct merging is kept, and the clustering recall rate is improved while the clustering precision is ensured.
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Description

technical field

[0001] The invention belongs to the technical field of big data processing, and specifically provides an incremental clustering method, device, equipment and storage medium based on human-computer interaction. Background technique

[0002] Clustering is the process of classifying data into different classes or clusters. Cluster analysis is an exploratory analysis. In the process of classification, people do not need to give a classification standard in advance. Cluster analysis can start from sample data. , to automatically classify. Cluster analysis has been widely used in business data analysis, pattern recognition, image processing and other fields.

[0003] How to efficiently obtain information from massive data has become the focus of research on clustering algorithms. In the current clustering algorithm, as the scale of data increases, the difficulty of data distribution increases, and the probability of high-scoring negative cases also increases, whi...

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Embodiment Construction

[0070] In order to make the purpose, technical solutions and advantages of the embodiments of the present invention more clear, the following will clearly and completely describe the technical solutions of the embodiments of the present invention in conjunction with the accompanying drawings. Obviously, the described embodiments are part of the embodiments of the present invention , but not all examples. Based on the embodiments of the present invention, all other embodiments obtained by persons of ordinary skill in the art without making creative efforts fall within the protection scope of the present invention.

[0071] read first figure 1 , figure 1 It is a flowchart of the main steps of the general incremental clustering method. Such as figure 1 As shown, general incremental clustering methods include:

[0072] Step S101: Obtain the data to be processed, the data to be processed includes new data and historical data;

[0073] Step S102: performing incremental clusteri...