公开(公告)号：US20160350664A1

公开(公告)日：2016-12-01

申请号：US15177237

申请日：2016-06-08

Applicant: SAS Institute Inc. ,  North Carolina State University

Inventor： Ravinder Devarajan ,  Jordan Riley Benson ,  David James Caira ,  Saratendu Sethi ,  James Allen Cox ,  Christopher G. Healey ,  Gowtham Dinakaran ,  Kalpesh Padia ,  Shaoliang Nie

IPC: G06N5/04 ,  G06F17/27 ,  G06F17/30 ,  G06N99/00

CPC classification number: G06F16/34 ,  G06F17/2735 ,  G06F17/2775 ,  G06F17/2785 ,  G06N3/084 ,  G06Q10/10 ,  G06Q50/01

Abstract: The results of electronic narrative analytics can be visualized. For example, an electronic communication that includes multiple narratives can be received. Each narrative can be segmented into respective blocks of characters. Multiple sentiments associated with the respective blocks of characters can be determined. Multiple sentiment patterns can be determined based on the multiple sentiments. The multiple sentiment patterns can be categorized into multiple sentiment pattern groups. Also, multiple semantic tags associated with the multiple sentiment patterns can be determined. Further, the multiple narratives can be categorized into multiple topic sets. A graphical user interface can be displayed visually indicating at least a portion of: the multiple sentiments, the multiple sentiment pattern groups, the multiple semantic tags, or the multiple topic sets.

Abstract translation: 电子叙事分析的结果可以被可视化。 例如，可以接收包括多个叙述的电子通信。 每个叙述都可以分割成各自的字符块。 可以确定与各个字符块相关联的多个情绪。 可以根据多种情绪来确定多种情绪模式。 多种情绪模式可以分为多种情绪模式组。 此外，可以确定与多个情绪模式相关联的多个语义标签。 此外，多个叙述可以分为多个主题集。 可以可视地显示图形用户界面，指示多个情绪，多个情绪模式组，多个语义标签或多个主题集中的至少一部分。

公开(公告)号：US20160350651A1

公开(公告)日：2016-12-01

申请号：US14966117

申请日：2015-12-11

Applicant: North Carolina State University ,  SAS Institute Inc.

Inventor： Ravinder Devarajan ,  Jordan Riley Benson ,  David James Caira ,  Saratendu Sethi ,  James Allen Cox ,  Christopher G. Healey ,  Gowtham Dinakaran ,  Kalpesh Padia

IPC: G06N3/08 ,  G06N5/02

CPC classification number: G06N5/02 ,  G06F17/27 ,  G06F17/2735 ,  G06F17/2775 ,  G06F17/2785 ,  G06N3/08 ,  G06N3/084 ,  G06N99/005

Abstract: Training data for training a neural network usable for electronic sentiment analysis can be automatically constructed. For example, an electronic communication usable for training the neural network and including multiple characters can be received. A sentiment dictionary including multiple expressions mapped to multiple sentiment values representing different sentiments can be received. Each expression in the sentiment dictionary can be mapped to a corresponding sentiment value. An overall sentiment for the electronic communication can be determined using the sentiment dictionary. Training data usable for training the neural network can be automatically constructed based on the overall sentiment of the electronic communication. The neural network can be trained using the training data. A second electronic communication including an unknown sentiment can be received. At least one sentiment associated with the second electronic communication can be determined using the neural network.

Abstract translation: 可以自动构建用于训练可用于电子情感分析的神经网络的训练数据。 例如，可以接收可用于训练神经网络并包括多个字符的电子通信。 可以接收包括映射到表示不同情绪的多个情绪值的多个表情的情感词典。 情绪词典中的每个表达式都可以映射到相应的情绪值。 可以使用情绪词典来确定电子通信的整体情绪。 可以根据电子通信的整体情绪自动构建可用于训练神经网络的训练数据。 可以使用训练数据训练神经网络。 可以接收包括未知情绪的第二电子通信。 可以使用神经网络来确定与第二电子通信相关联的至少一个情绪。