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authorCamil Staps2019-11-16 16:21:09 +0100
committerCamil Staps2019-11-16 16:21:09 +0100
commitad073854241d2c6def58c95af4dc19dc0a0c8c8b (patch)
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parentAdd reasoning behind advantage of hillclimbing over statistical analysis (diff)
parentUpdate names (diff)
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+# Baseline Rankings
+- On the left are the baseline rankings as they are given on the DBPedia-Entity
+repository
+- These baseline rankings are created by running the algorithms on a seemingly
+arbitrary set of fields of the DBPedia Index
+- Including some special fields that are noted on the right
+- Noteworthy is the attribute section which includes a blacklist of fields that
+are not used
+- The blacklist appears to be created through educated but subjective guesses
+- It is our goal to find out if this blacklist is ideal, or if it would be
+better if it was changed
+
+# HillClimbing
+- To achieve this, we intend to use Nordlys
+- Nordlys includes the scripts that run the algorithms given a configuration
+file, on the DBPedia Index.
+- It is to our understanding that we can modify this configuration file by
+adding and removing fields, and then run the algorithms
+- To achieve a maximum, we intent to use a hill climbing algorithm with binary
+weights; after all, we can only include or blacklist a field
+