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http://dx.doi.org/10.9708/jksci.2021.26.08.055

A Method for Compound Noun Extraction to Improve Accuracy of Keyword Analysis of Social Big Data  

Kim, Hyeon Gyu (Div. of Computer Science and Engineering, Sahmyook University)
Publication Information
Journal of the Korea Society of Computer and Information / v.26, no.8, 2021 , pp. 55-63 More about this Journal
Abstract
Since social big data often includes new words or proper nouns, statistical morphological analysis methods have been widely used to process them properly which are based on the frequency of occurrence of each word. However, these methods do not properly recognize compound nouns, and thus have a problem in that the accuracy of keyword extraction is lowered. This paper presents a method to extract compound nouns in keyword analysis of social big data. The proposed method creates a candidate group of compound nouns by combining the words obtained through the morphological analysis step, and extracts compound nouns by examining their frequency of appearance in a given review. Two algorithms have been proposed according to the method of constructing the candidate group, and the performance of each algorithm is expressed and compared with formulas. The comparison result is verified through experiments on real data collected online, where the results also show that the proposed method is suitable for real-time processing.
Keywords
Big data analysis; Social reviews; Keyword extraction; Morphological analysis; Compound noun extraction;
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