Semantic Scholar Open Access 2014 736 sitasi

Question Answering with Subgraph Embeddings

Antoine Bordes S. Chopra J. Weston

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Abstrak

This paper presents a system which learns to answer questions on a broad range of topics from a knowledge base using few hand-crafted features. Our model learns low-dimensional embeddings of words and knowledge base constituents; these representations are used to score natural language questions against candidate answers. Training our system using pairs of questions and structured representations of their answers, and pairs of question paraphrases, yields competitive results on a recent benchmark of the literature.

Topik & Kata Kunci

Computer Science

Penulis (3)

Antoine Bordes

S. Chopra

J. Weston

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APA MLA BibTeX

Bordes, A., Chopra, S., Weston, J. (2014). Question Answering with Subgraph Embeddings. https://doi.org/10.3115/v1/D14-1067

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Lihat di Sumber doi.org/10.3115/v1/D14-1067

Informasi Jurnal

Tahun Terbit: 2014
Bahasa: en
Total Sitasi: 736×
Sumber Database: Semantic Scholar
DOI: 10.3115/v1/D14-1067
Akses: Open Access ✓