Method of short text strategy mining based on sub-semantic space

Abstract

To solve the problem of identifying short text data accurately,a method of short text strategy mining based on sub-semantic space was proposed.Firstly,semantic space technology was used to solve the problem of “vocabularygap” and “data sparseness” in short text analysis.Then,based on clustering algorithm,the semantic space was divided into several sub-semantic spaces,and association rules were mined in the sub-semantic space,which improved the efficiency and quality of strategy generation.Finally,binary tree was used to merge strategies and generate the simplest strategy set.Experiments show that compared with the traditional classification model,the accuracy rate of the strategy set generated by the proposed scheme can achieve 85% when the false positive rate is 6.5%.In the processing of illegal short messages,using this technology to mine potential policy sets has strong coverage ability,high accuracy and strong practicability.

Keywords

• sub-semantic space;strategy extraction;short text;association rule mining;clustering