Knowledge Base Question Answering With Attentive Pooling for Question Representation

Knowledge Base Question Answering With Attentive Pooling for Question Representation

This paper presents a neural network model for a knowledge base (KB)-based single-relation question answering (SR-QA). This model is composed of two main modules, i.e., entity linking and relation detection. In each module, an embedding vector is computed from the input question sentence to calculat...

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Bibliographic Details
Main Authors: Run-Ze Wang, Zhen-Hua Ling, Yu Hu
Format: Article
Language:English
Published: IEEE 2019-01-01
Series:IEEE Access
Subjects:
Knowledge base question answering
entity linking
relation detection
attention mechanism
Online Access:https://ieeexplore.ieee.org/document/8684200/

Internet

https://ieeexplore.ieee.org/document/8684200/

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