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@@ -14,7 +14,7 @@ Please cite the paper if you use ln2sql.
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ln2sql is not the state-of-the-art tool for copyright reasons. It's just a quick & dirty Python wrapper but it has some speed optimizations.
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*[A data model is only learn from a parsing of a SQL dump file. Thus, <b>no database connection is needed</b>.](https://github.com/FerreroJeremy/ln2sql#database-input)
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*[A data model is only learned from a parsing of a SQL dump file. Thus, <b>no database connection is needed</b>.](https://github.com/FerreroJeremy/ln2sql#database-input)
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* In the paper, <arel="tt"href="http://www.cis.uni-muenchen.de/~schmid/tools/TreeTagger/">TreeTagger</a> is used to filter the words of the input sentence according to its POS tagging.
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In this way, a mapping between the keywords of the input sentence and the keywords of the data model can be performed.
@@ -179,4 +179,4 @@ The above diagram was modeled with <a rel="staruml" href="http://staruml.io/">St
This tool is licensed under a <arel="license"href="http://creativecommons.org/licenses/by-sa/4.0/">Creative Commons Attribution-ShareAlike 4.0 International License</a>.
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ln2sql is licensed under a <arel="license"href="http://creativecommons.org/licenses/by-sa/4.0/">Creative Commons Attribution-ShareAlike 4.0 International License</a>.
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