Al
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cd25ca1537
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[names] replace name affixes with both country/language and language-only variants
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2016-12-20 03:10:13 -05:00 |
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Al
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7436d9693a
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[names] adding new name_affixes call to replace both prefixes/suffixes in one call, using in GeoPlanet training and the generic AddressComponents normalizations
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2016-12-07 05:49:16 -05:00 |
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Al
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9386a999f6
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[names] adding country-specific affixes and only normalizing the word City as a suffix in UK/Ireland
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2016-12-07 05:37:25 -05:00 |
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Al
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79c9694e2d
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[names] Allowing for similarity-only normalization in name affixes
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2016-08-22 03:47:08 -04:00 |
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Al
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8b9e351961
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[names] Name affixes respect hyphens and lack of whitespace (for ideographic languages)
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2016-07-21 17:04:57 -04:00 |
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Al
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88b25a2d22
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[names] Adding name affix normalizations to a YAML config
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2016-07-21 17:04:57 -04:00 |
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Al
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68b70c351b
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[fix] /postal.text.normalize/geodata.text.normalize/
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2016-07-21 17:04:57 -04:00 |
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Al
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ee1aa564c4
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[normalization] normalize tokens should not replace digits by default
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2016-07-21 17:04:57 -04:00 |
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Al
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dd8f8b4d7b
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[fix] prefix/suffix regexes
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2015-12-05 18:41:22 -05:00 |
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Al
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2a4210f93f
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[osm] Stripping standard city prefixes/suffies e.g. Township of
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2015-12-05 15:42:22 -05:00 |
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Al
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f39090869e
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[fix] imports
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2015-10-31 14:22:45 -04:00 |
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Al
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f473ff0dad
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[fix] encoding, different file
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2015-10-31 14:18:47 -04:00 |
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Al
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3e43ac7255
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[polygons/osm] Adding a unified neighborhood reverse geocoder incorporating Zetashapes, OSM and Quattroshapes. Uses the new Soft TFIDF implementation to approximately match OSM names to Quattroshapes/Zetashapes names and geohash indices for more coarse point-in-polygon tests (OSM neighborhoods are stored as points not polygons, so need to match with a geometry from the other sources)
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2015-10-31 14:15:39 -04:00 |
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Al
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a38624ba59
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[similarity] Adding NameDeduper base class for deduping geographic names using the new Soft TFIDF similarity
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2015-10-31 00:57:02 -04:00 |
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Al
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a5c1296044
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[similarity] Adding Jaccard similarity with word frequencies instead of simple sets, better for ideographic scripts (Han, Hangul, etc.) in the absence of word segmentation since there may be many high frequency characters
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2015-10-30 14:35:38 -04:00 |
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Al
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cccc3e9cf5
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[similarity] Using Soft-TFIDF for approximate name matching. Soft-TFIDF is a hybrid string distance metric which balances local token similarities (using Jaro-Winkler similarity by default) allowing for slight spelling errors with global TFIDF statistics so that very frequent words don't affect the score as much
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2015-10-30 02:48:16 -04:00 |
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