Dawei Zhang
12 Papers
Dawei Zhang is an academic researcher. The author has contributed to research in topics: Computer science & Encryption. The author has an hindex of 2, co-authored 2 publications.
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Papers
Combining knowledge with deep convolutional neural networks for short text classification
Jin Wang,Zhongyuan Wang,Dawei Zhang,Jun Yan +3 more
- 01 Aug 2017
TL;DR: This paper proposes a framework based on convolutional neural networks that combines explicit and implicit representations of short text for classification and shows that the proposed method significantly outperforms state-of-the-art methods.
Microsoft Concept Graph: Mining Semantic Concepts for Short Text Understanding
Lei Ji,Lei Ji,Yujing Wang,Botian Shi,Dawei Zhang,Zhongyuan Wang,Jun Yan +6 more
- 23 May 2019
TL;DR: This paper introduces Microsoft Concept Graph, a knowledge graph engine that provides concept tagging APIs to facilitate the understanding of human languages and uses conceptualization models to represent text in the concept space to empower text-related applications.
Improving the Applicability of Knowledge-Enhanced Dialogue Generation Systems by Using Heterogeneous Knowledge from Multiple Sources
Si Wu,Minghui Wang,Ying Li,Dawei Zhang,Zhonghai Wu +4 more
- 11 Feb 2022
TL;DR: An MHKD-Seq2Seq framework, which can use different heterogeneous knowledge by identifying abstract-level knowledge behaviors, and a Diffuse-Aggregate scheme is used to process multiple knowledge simultaneously and produce a unified result.
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Ghost imaging-based optical multilevel authentication scheme using visual cryptography
TL;DR: Wang et al. as discussed by the authors proposed a multi-level authentication approach relying on ghost imaging and visual secret sharing, which can realize effective authentication under strong background noise and has a high discrimination capability, even though the image to be authenticated is very similar to the standard image.
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KSAM: Infusing Multi-Source Knowledge into Dialogue Generation via Knowledge Source Aware Multi-Head Decoding
TL;DR: KSAM uses multiple independent source-aware decoder heads to alleviate three challenging problems in infusing multi-source knowledge, namely, the diversity among different knowledge sources, the indefinite knowledge alignment issue, and the insufficient flexibility/scalability in knowledge usage.
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