BibTeX
@MISC{Wang_onlineegocentric,
author = {Hao Wang and Wu-jun Li},
title = {Online Egocentric Models for Citation Networks},
year = {}
}
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Abstract
With the emergence of large-scale evolving (timevarying) networks, dynamic network analysis (DNA) has become a very hot research topic in recent years. Although a lot of DNA methods have been proposed by researchers from different communities, most of them can only model snapshot data recorded at a very rough temporal granularity. Recently, some models have been proposed for DNA which can be used to model large-scale citation networks at a fine temporal granularity. However, they suffer from a significant decrease of accuracy over time because the learned parameters or node features are static (fixed) during the prediction process for evolving citation
Keyphrases
citation network online egocentric model snapshot data recent year learned parameter dna method node feature hot research topic dynamic network analysis significant decrease large-scale citation network large-scale evolving rough temporal granularity prediction process different community fine temporal granularity
