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Unknown - 2.0 GB - MD5: bf829ec77f73d57e9ce073b216135729
Unknown - 1.3 GB - MD5: 36f9239c9a5ec3a58ae540e8045beea7
Gzip Archive - 309.2 MB - MD5: 800846430f962e4c501b9ebc38ca72df
Tabular Data - 7.0 MB - 1 Variables, 179797 Observations - UNF:6:QDjFCPMzxIXpoNWCI+1eNQ==
Apr 28, 2023
Sood, Gaurav; Chintalapati, Rajashekar, 2022, "Piedomains: Predict the kind of content hosted by a domain using domain name and homepage text", https://doi.org/10.7910/DVN/YHWCDC, Harvard Dataverse, V5
Piedomains: Predict the kind of content hosted by a domain using domain name and homepage text. See: https://github.com/themains/piedomains
Gzip Archive - 365.2 MB - MD5: b9a930716f81c4c6c861e7b01d5a38d6
this models have 39 classes.
Gzip Archive - 170.4 MB - MD5: aaa9c255d24bfefeaa190caba26fd0ac
Version 4 has both text and cv models.
Dec 14, 2022
Sood, Gaurav; Laohaprapanon, Suriyan; Sanjeevi, Madhu; Tran, Khanh, 2018, "Parsed Indian Electoral Rolls", https://doi.org/10.7910/DVN/MUEGDT, Harvard Dataverse, V25, UNF:6:Jul7B4cP7aiLbKdAC1sM5g== [fileUNF]
For getting the pdfs of electoral rolls, see https://github.com/in-rolls/electoral_rolls. For scripts used to parse the electoral rolls, see https://github.com/in-rolls/parse_elex_rolls If you would like access to the electoral rolls, please fill out the following form. You will need to also get IRB approval from your respective university or insti...
Gzip Archive - 618.8 MB - MD5: ccabfe7848cc312930570893b0d2d48a
Unknown - 2.0 GB - MD5: 613ff8a2ffd75bd665b386e4438c75c4
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