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authorMartin Czygan <martin.czygan@gmail.com>2020-10-22 11:28:57 +0200
committerMartin Czygan <martin.czygan@gmail.com>2020-10-22 11:28:57 +0200
commit9aeacc07be8151a0d44d25cbe377c9f4a09a620a (patch)
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parentf01429bbc70cf8ed8cbc114956cd37236e65fd4a (diff)
downloadfuzzycat-9aeacc07be8151a0d44d25cbe377c9f4a09a620a.tar.gz
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update notes on clustering
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@@ -36,3 +36,21 @@ Numbers of clusters:
* [ ] do a SS like clustering, using title and author ngrams
* [ ] cluster by doi without "vX" suffix
+
+# Verification
+
+* we only need to look at identified duplicates, which will be a few millions
+* we want fast access to all release JSON blob via ident, maybe do a
+ "fuzzycat-cache" that copies relevant files into the fs, e.g.
+"~/.cache/fuzzycat/releases/d9/e4d4be49faafc750563351a126e7bafe29.json or via microblob (but http we do not need), or sqlite3 (https://www.sqlite.org/fasterthanfs.html)
+
+For verification we need to have the cached json blobs in some fast,
+thread-safe store. Estimated: 1K/s accesses, we still would need a few hours
+for a run.
+
+* [ ] find all ids we need, generate cache, maybe reduce number of fields
+* [ ] run verification on each cluster; generate a file of same format of
+ "verified" clusters; take note the clustering and verification method
+
+Overall, we can combine various clustering and verification methods. We can
+also put together a list of maybe 100-200 test cases and evaluate methods.