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of 31
pro vyhledávání: '"Beaver, Ian"'
Autor:
Chen, Xinyu, Tian, Jiannan, Beaver, Ian, Freeman, Cynthia, Yan, Yan, Wang, Jianguo, Tao, Dingwen
While both the database and high-performance computing (HPC) communities utilize lossless compression methods to minimize floating-point data size, a disconnect persists between them. Each community designs and assesses methods in a domain-specific m
Externí odkaz:
http://arxiv.org/abs/2312.10301
Autor:
Chen, Xinyu, Beaver, Ian
Mining the latent intentions from large volumes of natural language inputs is a key step to help data analysts design and refine Intelligent Virtual Assistants (IVAs) for customer service and sales support. We created a flexible and scalable clusteri
Externí odkaz:
http://arxiv.org/abs/2202.01211
Autor:
Chen, Xinyu, Beaver, Ian
Mining the latent intentions from large volumes of natural language inputs is a key step to help data analysts design and refine Intelligent Virtual Assistants (IVAs) for customer service. To aid data analysts in this task we present Verint Intent Ma
Externí odkaz:
http://arxiv.org/abs/2202.00802
Recent work in synthetic data generation in the time-series domain has focused on the use of Generative Adversarial Networks. We propose a novel architecture for synthetically generating time-series data with the use of Variational Auto-Encoders (VAE
Externí odkaz:
http://arxiv.org/abs/2111.08095
Autor:
Beaver, Ian
When reviewing the performance of Intelligent Virtual Assistants (IVAs), it is desirable to prioritize conversations involving misunderstood human inputs. These conversations uncover error in natural language understanding and help prioritize and exp
Externí odkaz:
http://pqdtopen.proquest.com/#viewpdf?dispub=10816823
In (Yang et al. 2016), a hierarchical attention network (HAN) is created for document classification. The attention layer can be used to visualize text influential in classifying the document, thereby explaining the model's prediction. We successfull
Externí odkaz:
http://arxiv.org/abs/1808.02113
We create and release the first publicly available commercial customer service corpus with annotated relational segments. Human-computer data from three live customer service Intelligent Virtual Agents (IVAs) in the domains of travel and telecommunic
Externí odkaz:
http://arxiv.org/abs/1708.05449
Akademický článek
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Autor:
Beaver, Ian, Mueen, Abdullah
Publikováno v:
AI Magazine; Vol. 42 No. 4: Winter 2021; 29-42
With the rise of intelligent virtual assistants (IVAs), there is a necessary rise in human effort to identify conversations containing misunderstood user inputs. These conversations uncover error in natural language understanding and help prioritize
Externí odkaz:
https://explore.openaire.eu/search/publication?articleId=doi_dedup___::3dc693b5751a5030a91b8bf929268270
https://doi.org/10.1609/aaai.12024
https://doi.org/10.1609/aaai.12024
Akademický článek
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