Result for 66939F11854B97EA40FF925AEBD94499DFEA0F70

Query result

Key Value
FileName./usr/lib64/R/library/ELMSO/Meta/package.rds
FileSize1309
MD598EC730095026FC4CF71FF76A0105EDB
SHA-166939F11854B97EA40FF925AEBD94499DFEA0F70
SHA-2563E36206FFED43B5B98256B744C014CD40C8B3CB27DE38F05211AC1B1E21F6C7E
SSDEEP24:XLyfbYlg/5qyFlfYvIMpMKlfMWban2fnxrjozqXLDvWB/N88qu22ZNuFcdzvEStN:XLyDYlgRvfYvnFUl0nxjozm/vi/N88qY
TLSHT12821CBC796E25377D37608F5178458909A54E93232D4061D131E8414F861387F7E356C
hashlookup:parent-total1
hashlookup:trust55

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Parents (Total: 1)

The searched file hash is included in 1 parent files which include package known and seen by metalookup. A sample is included below:

Key Value
MD58DC5D211A05E1CF1E9CA248B00FF5048
PackageArchx86_64
PackageDescriptionAn implementation of the algorithm described in "Efficient Large- Scale Internet Media Selection Optimization for Online Display Advertising" by Paulson, Luo, and James (Journal of Marketing Research 2018; see URL below for journal text/citation and <http://faculty.marshall.usc.edu/gareth-james/Research/ELMSO.pdf> for a full-text version of the paper). The algorithm here is designed to allocate budget across a set of online advertising opportunities using a coordinate-descent approach, but it can be used in any resource-allocation problem with a matrix of visitation (in the case of the paper, website page- views) and channels (in the paper, websites). The package contains allocation functions both in the presence of bidding, when allocation is dependent on channel-specific cost curves, and when advertising costs are fixed at each channel.
PackageNameR-ELMSO
PackageRelease2.21
PackageVersion1.0.1
SHA-1790F81FDE4A16BB742973A1F1BF029359F6412F2
SHA-25620D944660326116F8A696563EF9D033E392D0041FDCF076649D46E8A6B4AA9F0