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authorMartin Czygan <martin.czygan@gmail.com>2021-08-21 13:19:20 +0200
committerMartin Czygan <martin.czygan@gmail.com>2021-08-21 13:19:20 +0200
commitd6b744dbbcd8e8e13ecb03fe267f59bceeda933a (patch)
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parentf9d1857a6940e5beca5f08dc41193ad70672827b (diff)
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@@ -21,8 +21,10 @@ For example:
2. it refereces articles and web pages, books, etc; we can get this information from the data or grobid
3. we lookup the title on P in some existing data store; we lookup normalized
title in some normalized data store; we could just exact of fuzzy match
- against elasticsearch; we generate match candidates, e.g. where all references live
-4. we verify matches
+ against elasticsearch; we generate match candidates, e.g. where all references
+ live (here: batch requires high performance, whereas continuous would be about
+ order of 100K per day ).
+4. we verify matches (here: batch needs to be fast again; 1M/min or the like)
5. we update the index and add new edges between document
6. we add all references found into the "reference store"