Mining method and device for highly-expected weight item set of valid time and processing equipment

Abstract

The embodiment of the invention provides a mining method and device for a highly-expected weight item set of valid time and processing equipment. The method comprises the steps that at least one target event corresponding to a to-be-processed item set is determined; a time validity value of the to-be-processed item set in an uncertain database is determined; an expected support degree of the to-be-processed item set is determined; the expected support degree of the to-be-processed item set is multiplied with an item set weight value of the to-be-processed item set, and an expected weight support degree of the to-be-processed item set is determined; and if the time validity value of the to-be-processed item set in the uncertain database is not smaller than a predefined minimum time validitythreshold value and the expected weight support degree of the to-be-processed item set is not smaller than a product of a predefined minimum expected weight threshold value and the sum of events in the uncertain database, it is determined that the to-be-processed item set is the highly-expected weight item set of the valid time. Through the embodiment, mining of the highly-expected weight item set of the valid time in the uncertain database is realized.

Description

technical field [0001] The present invention relates to the technical field of data processing, in particular to a method, device and processing equipment for efficient time high expected weight item set mining. Background technique [0002] At present, when recommending content that users are interested in (such as webpages, news, commodities, etc.), and mining frequently searched hot and high-frequency words, it is often necessary to dig out high-expectation weight itemsets with effective time from the database; effective time The high expected weight item set of refers to the item set with high timeliness and expected frequency in the database, which means the recently effective high expected weight item set in the database. It should be noted that the database usually records at least one transaction, news, etc., each transaction includes at least one data item, and in order to represent the association rules between data items in the database, at least one data item wil...

AI Technical Summary

Problems solved by technology

[0003] At present, mining algorithms based on weight factors are generally used to mine high-expectation weight item sets with effective time from the database. These algorithms are generally simple to mine item sets based on weight factors, and can only be used for databases that store accurate data. However, in the actual mining process, the types of data are different, and the data in the database often contains uncertainty (that is, the database often stores uncertain data); (Uncertain database for short) When mining high expected weight item sets with effective time, the current mining algorithms based on weight factors are not applicable; for example, a database stores transaction records of the past three years, and the data items in it are different Among them, the weight value corresponding to the notebook is 0.4, the weight value corresponding to the bread is 0.001, and the weight value corresponding to the electric fan is 0.05. It can be seen that the weight values ​​corresponding to the data items are different. If you need to dig out six According to the current mining algorithm based on weight factors, it is impossible to mine the uncertain database, which will lead to the situation that the high expected weight item set of effective time cannot be mined.

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