Knowledge Commons of Institute of Automation,CAS
Biological Neuron Coding Inspired Binary Word Embeddings | |
Wang, Yuwei1,2; Zeng, Yi1,2,3,4; Tang, Jianbo1,2; Xu, Bo1,2,3 | |
发表期刊 | COGNITIVE COMPUTATION |
ISSN | 1866-9956 |
2019-10-01 | |
卷号 | 11期号:5页码:676-684 |
摘要 | Word embeddings are the semantic representations of the words. They are derived from large corpus and work well on many natural language tasks, with one downside of costing large memory space. In this paper, we propose binary word embedding models based on inspirations from biological neuron coding mechanisms, converting the spike timing of neurons during specific time intervals into binary codes, reducing the space and speeding up computation. We build three types of models to post-process the original dense word embeddings, namely, the homogeneous Poission processing-based rate coding model, the leaky integrate-and-fire neuron-based model, and the Izhikevich's neuron-based model. We test our binary embedding models on word similarity and text classification tasks of five public datasets. The experimental results show that the brain-inspired binary word embeddings (which reduce approximately 68.75% of the space) get similar results to original embeddings for word similarity task while better performance than traditional binary embeddings on text classification task. |
关键词 | Word embeddings Neuron coding Spiking neural networks |
DOI | 10.1007/s12559-019-09643-1 |
关键词[WOS] | NETWORKS ; CELLS ; INFORMATION ; MODEL |
收录类别 | SCI |
语种 | 英语 |
资助项目 | Major Research Program of Shandong Province[2018CXGC1503] ; CETC Joint Fund[6141B08010103] ; Beijing Municipality of Science and Technology[Z181100001518006] ; Strategic Priority Research Program of Chinese Academy of Sciences[XDB32070100] ; Strategic Priority Research Program of Chinese Academy of Sciences[XDB32070100] ; Beijing Municipality of Science and Technology[Z181100001518006] ; CETC Joint Fund[6141B08010103] ; Major Research Program of Shandong Province[2018CXGC1503] |
WOS研究方向 | Computer Science ; Neurosciences & Neurology |
WOS类目 | Computer Science, Artificial Intelligence ; Neurosciences |
WOS记录号 | WOS:000495244800006 |
出版者 | SPRINGER |
七大方向——子方向分类 | 类脑模型与计算 |
国重实验室规划方向分类 | 认知机理与类脑学习 |
引用统计 | |
文献类型 | 期刊论文 |
条目标识符 | http://ir.ia.ac.cn/handle/173211/28877 |
专题 | 脑图谱与类脑智能实验室_类脑认知计算 |
通讯作者 | Zeng, Yi |
作者单位 | 1.Chinese Acad Sci, Inst Automat, Beijing, Peoples R China 2.Univ Chinese Acad Sci, Beijing, Peoples R China 3.Chinese Acad Sci, Ctr Excellence Brain Sci & Intelligence Technol, Shanghai, Peoples R China 4.Chinese Acad Sci, Inst Automat, Natl Lab Pattern Recognit, Beijing, Peoples R China |
第一作者单位 | 中国科学院自动化研究所 |
通讯作者单位 | 中国科学院自动化研究所; 模式识别国家重点实验室 |
推荐引用方式 GB/T 7714 | Wang, Yuwei,Zeng, Yi,Tang, Jianbo,et al. Biological Neuron Coding Inspired Binary Word Embeddings[J]. COGNITIVE COMPUTATION,2019,11(5):676-684. |
APA | Wang, Yuwei,Zeng, Yi,Tang, Jianbo,&Xu, Bo.(2019).Biological Neuron Coding Inspired Binary Word Embeddings.COGNITIVE COMPUTATION,11(5),676-684. |
MLA | Wang, Yuwei,et al."Biological Neuron Coding Inspired Binary Word Embeddings".COGNITIVE COMPUTATION 11.5(2019):676-684. |
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