Text Feature Extraction Based on Concept Relations
WEN Bilong
LI Naifeng
REN Xiuying
FENG Xiang
LV Pengquan
Abstract：Owing to the problem that the method that TF‐IDF text feature extraction based on word frequency statistic lacks the concept relations in the text ,there are some problems in the text feature extraction ,such as the redundancy of con‐cept and unclear feature .The method of the word frequency statistics based on similarity of ontology concepts is introduced . The frequency of feature element using semantic similarity between text elements is applied .It emphasizes the semantic con‐tribution of feature element ,eliminating redundancy of feature ,and enhancing independence of the elements of the features collection .Finally ,combined with the co‐occurrence characteristics of the concepts of the text ,it accomplishes to deal with ignored problems that some important feature elements through word frequency statistics lead to ignoring .Consequently ,it achieves the goal that it can extract text accurately and efficiently .
Keywords：text featureword frequency statisticssimilarity of ontology conceptsco-ocurrence features
Publication Date：2014-01-01
Online Publishing Date：2025-08-15(First online date of this platform, not the publication date of the document)
Pages：4( 2066-2068,2163 )