https://jp.techcrunch.com/2011/05/24/20110523sonar-finds-you-the-most-relevant-people-in-the-room/
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32. â—Geo::Hash (http://search.cpan.org/dist/Geo-Hash/) â—ベンãƒãƒžãƒ¼ã‚¯ â—隣接ã™ã‚‹geohashを求ã‚ã‚‹adjacentメソッドãŒã‚ã‚‹ geohash Encode Benchmark: timing 500000 iterations of Geo::Hash encode, Geo::Hash::XS encode... Geo::Hash encode: 137 wallclock secs (136.95 usr + 0.00 sys = 136.95 CPU) @ 3650.97/s (n=500000) Geo::Hash::XS encode: -1 wallclock secs ( 0.66 usr + 0.00 sys = 0.66 CPU) @ 757575.76/s (n=500000) Rate Geo::Has
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Google Places API Could Do For Check-ins What Google Maps Did For Maps
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Location, Location, Location: 5 Big Predictions for 2010
Location, Location, Location: 5 Big Predictions for 2010 In 2009, location-sharing applications finally emerged in user-friendly formats, altering the way we think about where we are and helping us understand more of the meaning behind the data in aggregate. Technology early adopters showed a predilection towards mobile location-based games, discovering that check-ins could mean something and that
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https://jp.techcrunch.com/2010/10/19/jp-20101018-photo-sharing-apps-phototreats-got-100k-download-after-4-days/
https://jp.techcrunch.com/2010/08/18/20100816barcode-hero/
https://jp.techcrunch.com/2010/08/11/20100810neer-geo-fence/
Checking in with the Places API
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