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http://dx.doi.org/10.9708/jksci.2015.20.4.017

Two-Phase Clustering Method Considering Mobile App Trends  

Heo, Jeong-Man (Dept. of Game Design & Development, SangMyung University)
Park, So-Young (Dept. of Game Design & Development, SangMyung University)
Publication Information
Journal of the Korea Society of Computer and Information / v.20, no.4, 2015 , pp. 17-23 More about this Journal
Abstract
In this paper, we propose a mobile app clustering method using word clusters. Considering the quick change of mobile app trends, the proposed method divides the mobile apps into some semantically similar mobile apps by applying a clustering algorithm to the mobile app set, rather than the predefined category system. In order to alleviate the data sparseness problem in the short mobile app description texts, the proposed method additionally utilizes the unigram, the bigram, the trigram, the cluster of each word. For the purpose of accurately clustering mobile apps, the proposed method manages to avoid exceedingly small or large mobile app clusters by using the word clusters. Experimental results show that the proposed method improves 22.18% from 57.48% to 79.66% on overall accuracy by using the word clusters.
Keywords
Mobile App Clustering; Word Clustering; Clustering Algorithm; Text Analysis;
Citations & Related Records
Times Cited By KSCI : 6  (Citation Analysis)
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