Systeme und Verfahren zur Menschlichen Inspirierten Einfachen Fragenbeantwortung (hisqa)

Details

Veröffentlichungs-Nr.

EP3156949

Aktenzeichen

EP16193941

Anmeldetag

14. Oktober 2016

Veröffentlichung

21. Juni 2017

Rechtsraum

EP

IPC

G06N99/00// G06N3/04G06F17/30G06N7/00

Abstract

Described herein are systems and methods for determining how to automatically answer questions like "Where did Harry Potter go to school?" Carefully built knowledge graphs provide rich sources of facts. However, it still remains a challenge to answer factual questions in natural language due to the tremendous variety of ways a question can be raised. Presented herein are embodiments of systems and methods for human inspired simple question answering (HISQA), a deep-neural-network-based methodology for automatic question answering using a knowledge graph. Inspired by human's natural actions in this task, embodiments first find the correct entity via entity linking, and then seek a proper relation to answer the question-both achieved by deep gated recurrent networks and neural embedding mechanism.

Anmelder

Firma

Baidu USA LLC

Land

🇺🇸 USA

Fachgebiete