Elasticsearch and Fuzzy Name Matching Meetup, World Tour

Normalization is crucial to high quality search results — who wants irrelevant variations between queries and documents leading to missed hits (e.g., “celebrity” v. “celebrities”)? Normalizing dictionary words works, but what if your application focuses on names? Whether you’re tackling log analysis, e-commerce, watch list screening or other applications, names are often the key. Can you find “Abdul Jabbar, Karim” if you search for “Kareem AbdalJabar” or “كريم عبد الجبار”?

Applications using Elasticsearch provide some fuzziness by mixing its built-in edit-distance matching and phonetic analysis with more generic analyzers and filters (see example #1 or #2). We’ve tried to go beyond that to provide both better matching and a simpler integration. We use a custom Mapper and Score Function so that linguistic nuances can be handled behind-the-scenes. We’ll talk about how we built this sort of plug-in for Rosette, its customization, and its connection to broader trend of entity-centric search.



Where, When?


Thursday, June 18th, 6pm
Basis Technology, Cambridge HQ
One Alewife Center,
Cambridge, MA 02140


Speakers: Basis Technology –  Brian Sawyer & Chris Mack


Washington D.C.

Thursday, June 25th, 6pm
We Work Dupont Circle
1875 Connecticut Ave NW, 10th Floor
Washington, DC 20008


Speaker 1: Basis Technology –  Graham Morehead
Speaker 2: Search Technologies



Tuesday, July 21st,  6.30pm
Golden House

30 Great Pulteney Street, W1F 9NN
London, GB


Speaker 1: The Filter
Speaker 2: Basis Technology


Tel Aviv

Wednesday, July 22nd, 6pm

WeWork Dubnov
7 Dubnov, Tel Aviv, 6473207


Speaker 1: Basis Technology
Speaker 2: Cellebrite
Speaker 3: We Ankor


Paris, France

Wednesday, July 29th
La Mutinerie
29 rue de Meaux, Paris 19e


Speaker 1: Basis Technology
Speaker 2: Canal +