Method and system for mining association patterns of Chinese feature words based on dynamic item weights

Abstract

The invention discloses a Chinese feature word association pattern mining method based on dynamic project weight and a system thereof. The method comprises the following steps: preprocessing by a Chinese text preprocessing module, and constructing a Chinese text database and a feature word project library; utilizing a Chinese feature word candidate item set generating and pruning module to generate a matrix weighting feature word candidate item set, pruning the candidate item set by adopting a new matrix weighting item set pruning method to obtain a final matrix weighting feature word candidate item set; utilizing a Chinese feature word frequent item set generation module to calculate item set weight so as to obtain a feature word frequent item set; and utilizing a Chinese feature word association mode generating and result displaying module to generate all proper subsets of the item set, mining an effective association pattern through the simple calculation and comparison of the item set weight, and displaying to a user to use. The invention exhibits favorable pruning performance, the candidate item set and the mining time of the invention are obviously reduced and shortened, mining efficiency is greatly improved, the pattern of the invention is applied to an information retrieval field, and information query performance can be improved.

Description

technical field [0001] The invention belongs to the field of data mining, specifically a matrix-weighted Chinese feature word association pattern mining method based on dynamic item weights and a mining system thereof, which is applicable to feature word association pattern discovery in Chinese text mining and Chinese text information retrieval query expansion, In the field of cross-language information retrieval of text, the feature word association pattern mined by it can be used as a source of high-quality extended words and applied to web search engines, which will help improve its information retrieval query performance. Background technique [0002] At present, mining methods based on item frequency and mining methods based on fixed item weights have been widely studied and applied, while mining methods based on dynamic item weights are rarely reported. The mining method based on dynamic item weight has important application value and broad application prospect in text...

AI Technical Summary

Problems solved by technology

Its defect is that it only pays attention to the frequency of items and ignores the existence of item weights, resulting in an increase in redundant, invalid and uninteresting association modes

Its defect is that it does not consider the change of item weight with the change of transaction records, that is, ignores the change of item weight, and cannot solve the data mining problem with the characteristics of item weight change

The disadvantage of the existing mining method based on dynamic item weights is that the number of association patterns it mines is still huge, and there are many uninteresting, false and invalid association patterns, which increases the difficulty for users to choose the desired pattern

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