%PDF-1.4
%
1 0 obj
<>stream
Topic models,latent Dirichlet allocation,fisheries science,fisheries models,research trends
iText 4.2.0 by 1T3XT
application/pdf
10.1080/23308249.2017.1416331
en
Taylor & Francis
Reviews in Fisheries Science and Aquaculture, 2018. doi:10.1080/23308249.2017.1416331
Topic models
latent Dirichlet allocation
fisheries science
fisheries models
research trends
Using Machine Learning to Uncover Latent Research Topics in Fishery Models
Shaheen Syed
Charlotte Teresa Weber
Journal
Reviews in Fisheries Science & Aquaculture
Copyright Taylor & Francis
2330-8249
2330-8257
26
3
319
336
10.1080/23308249.2017.1416331
https://doi.org/10.1080/23308249.2017.1416331
VoR
Arbortext Advanced Print Publisher 10.0.1062/W Unicode
2018-05-04T04:35:03-07:00
2018-05-02T07:41:46+05:30
2018-05-04T04:35:03-07:00
uuid:3d73aa0b-c00c-4d56-af6e-7aeaf0ead6e4
uuid:ed14faac-9be5-4b74-9e60-c0b859442fce
2018-01-16truewww.tandfonline.com10.1080/23308249.2017.1416331www.tandfonline.comtrue2018-01-1610.1080/23308249.2017.1416331
endstream
endobj
4 0 obj
<>stream
xYId5ׯ }PK]܀8AÅI̥5z]eq~v_~}{f1ͺʿ8K{Ŀ2{Gc.藉v:d
~1GX7znRK_kUS,>SV;MwbwiZv*<7
hd9N[s5״|MKL#4: ɭm\OONN3WDŽQ
ΨWOJ}-O4SOCN69D8M-b).9 t~QN}2L'HRVK8|aV%m
̒}'욵"FbO_V%+"_J/r @Ku)(3 83I