Case Study Summary:
The Passenger Name List application was developed by ai-one for one of the largest airline ground handling services company in the world.
The PNL Matcher is being used by airlines at the JFK, FRA, and ZHR airports to efficiently and accurately match a PNL (Passenger Name List) with the different suspect lists (no-fly list) supplied by official sources such as the U.S. Department of Homeland Security (DHS) Secure Flight Program.
This application uses the core ai-one™ technology in a limited but very effective way. The challenge in this area is the need to comply quickly with new U.S. DHS requirements to effectively screen passengers before boarding a flight.
The challenge for such an application is, when a ticketing agent creates a ticket for a passenger from a country that does not use the western alphabetic character set and phonetically spells the name. Since the spelling could be very different from different agents, the software has to be intelligent enough to find and match suspect passengers to the DHS list. Additionally phonetic use of characters is varies from country to country but must meet U.S. requirements for quality.
PNL Benefits:
- Fast, very accurate response to a ticket agent
- Phonetic spelled names can be matched with compliance to all regulations
- Easy to add new lists
- Works in any language or character set (language agnostic)
Topic:
Visualize all associations within written text
Kind:
Custom implementation of Topic-Mapper API
Status:
Solutions installed runs since its implementation in 2007 productive
Partner:
Rico Barandun, Product Manager
Application areas:
- Pattern Matching
- Security
Target Industries
- Transportation
- Homeland security
- Law enforcement
Tags: Case Study, DHS No Fly List, language agnostic, Machine Learning API, phonetic matching, Secure Flight Program