Data classification method and device

Abstract

The invention relates to the field of data processing and discloses a commodity classification method and device, which are used for increasing the executing efficiency of a commodity classification flow. The method comprises the following steps of: acquiring relevant data of commodities to be classified and extracting commodity titles from the data; dividing participles of commodity titles respectively and determining the weight of each participle, wherein the weight of each participle is used for representing the history occurrence rate of the participle; selecting participles of which the weight values are consistent with a preset condition respectively specific to different commodities to constitute a participle sequence; and comparing the participle sequences selected specific to thecommodities and combining relevant data of commodities having the same participle sequence. By adopting the method and the device, the quantity of relevant data of commodities needing to be processedis reduced greatly, commodity classification can be realized quickly and accurately in a short period of time, the executing efficiency of the commodity classification flow is increased effectively, the management complexity of relevant data of the commodities is lowered, and the operation load of a system is lowered.

Description

technical field [0001] The present application relates to the field of data processing, in particular to a data classification method and device. Background technique [0002] In an e-commerce website, various product data are usually stored in the form of text, data tables, and the like. An e-commerce website needs to manage tens of millions of product data. Therefore, how to classify the product data according to the information content it describes, and manage similar product data in a unified manner, so as to reduce the management complexity of the system and reduce the burden on the system. The operating load is the first issue that needs to be considered when operating an e-commerce website. [0003] At present, in various e-commerce websites, clustering algorithms are usually used to classify various product data, that is, according to a series of preset rules and conditions, the product data is divided into multiple categories through similarity analysis. In the pr...

AI Technical Summary

Problems solved by technology

Therefore, using the hierarchical clustering algorithm to classify the relevant data of various commodities in the e-commerce website requires a very large amount of calculation, so that it cannot be completed by a single machine, and a server cluster is required for unified calculation.

Obviously, this will greatly waste system resources and consume a lot of computing time, so that the classification of product-related data cannot be completed in a timely and effective manner, reducing the execution efficiency of the product-related data classification process

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