Abstract: Visual-textual sentiment analysis aims to predict sentiment with the input of a pair of image and text, which poses a challenge in learning effective features for diverse input images. To ...

The North Carolina Tar Heels lost to the Duke Blue Devils on Saturday night, with there being no margin of error. The Tar Heels needed to win this game, but in the ...

Have you ever wondered how businesses sift through mountains of customer feedback to uncover what truly matters? Imagine receiving hundreds, if not thousands, of ...

Three business analytics case studies were undertaken, encompassing market basket analysis, customer segmentation, and campaign management. SAS Visual Data Mining and Machine Learning on SAS Viya was ...

Analyzed customer churn using transaction data. Built ML model to predict lapses. Dataset includes customer status, collection/redemption info, and program tenure. Delivered business presentation ...

The ECO-SAM utilizes a pre-trained BERT encoder to obtain semantic embedding of input texts and then leverages a self-attention mechanism to model the semantic correlation between emotions.

Better customer retention. By identifying dissatisfaction early, sentiment analysis aids proactive interventions, which helps to reduce churn and improve loyalty. Transformative business insights.

Microsoft has introduced text analysis features in Excel aimed at helping users derive insights from surveys, reviews, and other textual data with ease. Copilot is a new feature in Excel that can help ...

As humans, we use a variety of skills to determine how someone is feeling. We listen to what they’re saying, watch their expression and body language, listen to changes in the tone of their voice, and ...