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Wednesday, March 13 • 4:30pm - 5:00pm
Translating Natural Language to Graph Queries for Financial Crime Investigation

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Financial crime investigation is a labor-intensive task. Oracle provides tools (e.g., FCCM Studio) that allow investigators to analyze whether a case involves fraud. To do so, investigators query and analyze databases containing financial transactions through an easy-to-use interface. However, often this interface does not provide enough flexibility. In such cases, analysis may require the development of database queries in SQL or PGQL (for Graph databases). Having to do so is not desirable because (1) it requires business users to learn a (complex) query language and (2) business users need to know about the underlying database schema. To remedy this situation, we have developed a natural language interface to graph databases that provides business users with a natural way to query the databases. In this talk, we present NL2PGQL, which translates sentences in natural language into a PGQL query that can be executed using Oracle Spatial and Graph.



Speakers
avatar for Matthias Brantner

Matthias Brantner

Research Director, Oracle
Matthias is a Research Director at Oracle Labs. His research interests are at the cross road of data processing and language compilers. He holds a PhD from the University of Mannheim, Germany.
avatar for Jinha Kim

Jinha Kim

Principal Member of Technical Staff, Oracle
Jinha Kim is a Principal Member of Technical Staff at Oracle Labs. He is interested in graph analytics and machine learning from designing through implementation to application. He obtained his PhD from Pohang University of Science and Technology, South Korea.

Wednesday March 13, 2019 4:30pm - 5:00pm PDT
2-Rm 103
  Spatial and Graph   Artificial Intelligence and Machine Learning