InteractionTrendData Time Series Data Analysis_TadGAN

Time Series Data Analysis_TadGAN

[Prior Research Team, Ji-Hyun Song] The TadGAN algorithm developed by the MIT research team is known to have better performance than previously known models in detecting anomalies by analyzing time series data. Currently, many companies researching anomaly detection are working in various fields (financial…

TrendData Time Series Data Analysis_TadGAN

The value of a data specialist

[Service Development Team Jeon Jeon Jeon] The digital transformation of companies accelerated by Corona 19 continues to increase the value of data. The need for change in various industries as well as specialized IT companies is raising ransom money for data specialists.

Data Time Series Data Analysis_TadGAN

Ubuntu Dialog Corpus

Building a conversation system that allows humans to have natural-looking conversations with virtual agents is a difficult task in natural language processing and is the basis for much ongoing research. Ubuntu Dialogue Corpus addresses various Ubuntu-related issues…

InteractionData Time Series Data Analysis_TadGAN

Korean profanity text dataset

We share a set of Korean profanity data collected and labeled by Joonhee Jo. It is gathered from multiple communities, and seems to be suitable for evaluation of real-world data. Below is a description of the data set: The Data Description statement is classified as swearword...

Data Time Series Data Analysis_TadGAN

MELD: Multimodal EmotionLines Dataset

Multimodal EmotionLines Dataset (MELD) is a multimodal extension of EmotionLines, an emotionally labeled dialogue data set. MELD contains the same dialog instances available in EmotionLines, but audio and visual forms along with text…