Export to

• Google Calendar
• iCalendar file
• hCalendar markup
  <div class="vevent h-event"> <h1 class="summary p-name">pdxrlang meetup: Probabilistic Approaches to Multi-dimensional Fuzzy Joins: A GeoSpatial Example</h1> <div class='date'><time class="dtstart dt-start" title="2016-08-09T18:30:00" datetime="2016-08-09T18:30:00">Tuesday, August 9, 2016 from 6:30</time>–<time class="dtend dt-end" title="2016-08-09T20:00:00" datetime="2016-08-09T20:00:00">8pm</time></div> <div class="location vcard p-location h-card"> <a class="url" href='http://calagator.org/venues/202393905'><span class='fn org p-name'>Mozilla</span></a> <div class="adr p-adr h-adr"> <div class="street-address p-street-address">1120 NW Couch St., Suite 320</div> <span class="locality p-locality">Portland</span> , <span class="region p-region">Oregon</span> <span class="postal-code p-postal-code">97209</span> <div class="country-name p-country-name">US</div> (<a href='https://maps.google.com/maps?q=1120%20NW%20Couch%20St.,%20Suite%20320,%20Portland%20Oregon%2097209%20US'>map</a>) </div> </div> <div class="description p-description"> <p>Speaker: De'Mel Mojica</p> <p>Abstract: This talk will be on a general approach to automatically join large-scale, geospatial data across distinct data sets, using a mix between Levenshtein Distance thresholds and Haversine Distance thresholds. This approach permits joining multiple data sets without the need to provide ad hoc normalization conventions for each data resource. In addition, this approach can be generalized beyond a geospatial field and applied any domain which requires joining across two or more non-identical dimensions.</p> <p>We'll visit a local watering hole afterwards.</p> </div> <h3>Links</h3> <ul> <li><a class="url u-url" href="http://www.meetup.com/portland-r-user-group/events/230860024/">Website</a></li> </ul> </div>