Time-Varying Dynamic Topic Model: A Better Tool for Mining Microblogs at a Global Level
نویسندگان
چکیده
Inthispapertheauthorsbuildonpriorliteraturetodevelopanadaptiveandtime-varyingmetadataenableddynamictopicmodel(mDTM)andapplyittoalargeWeibodatasetusinganonlineGibbs samplerforparameterestimation.Theirapproachsimultaneouslycapturesthemaximumnumberof inherentdynamicfeaturesofmicroblogstherebysettingitapartfromotheronlinedocumentmining methodsintheextantliterature.Insummary,theauthors’resultsshowabetterperformanceofmDTM intermsofthequalityoftheminedinformationcomparedtopriorresearchandshowcasesmDTMas apromisingtoolfortheeffectiveminingofmicroblogsinarapidlychangingglobalinformationspace. KeywoRDS Dynamic Topic Models, Gibbs Sampler, LDA, Metadata, Microblogs, Microposts, Perplexity Measure, Text Mining
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ورودعنوان ژورنال:
- JGIM
دوره 26 شماره
صفحات -
تاریخ انتشار 2018