Fine‐Grained Mobile Application Clustering Model Using Retrofitted Document Embedding

Fine‐Grained Mobile Application Clustering Model Using Retrofitted Document Embedding

In this paper, we propose a fine‐grained mobile application clustering model using retrofitted document embedding. To automatically determine the clusters and their numbers with no predefined categories, the proposed model initializes the clusters based on title keywords and then merges similar clus...

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Bibliographic Details
Main Authors: Yeo‐Chan Yoon, Junwoo Lee, So‐Young Park, Changki Lee
Format: Article
Language:English
Published: Electronics and Telecommunications Research Institute (ETRI) 2017-08-01
Series:ETRI Journal
Subjects:
Document embedding
Text clustering
Deep learning
Online Access:https://doi.org/10.4218/etrij.17.0116.0936

Internet

https://doi.org/10.4218/etrij.17.0116.0936

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