Communication mining involves the automated extraction, analysis, and interpretation of insights from various forms of textual communication data, such as emails, chat logs, social media interactions, and documents. Through techniques like natural language processing (NLP), sentiment analysis, and entity recognition, communication mining enables organizations to uncover valuable information, patterns, and trends within their vast troves of unstructured text data.

Agenda:

• Introduction to Communication Mining
• Definition and importance of communication mining.
• Overview of its applications and benefits.
• Labels and Entities for Insight Capture
• Explanation of using labels and entities to capture insights from communication data.
• Discussion on their significance and application in communication mining.
• Understanding Data Sources
• Discuss the types of communication data sources (emails, chat logs, social media, etc.).
• Gen-Ex Features
  
• Introduction to the newly introduced Gen Ex features.
• Discussion on their functionalities and benefits.
• Describe or Prompt What You Want to See in the Filters
• Explanation of how to describe or prompt specific filters.
• Demonstrate how to apply these prompts to refine data analysis.
• Demonstration
• Live demonstration of using labels and entities for communication mining using a sample dataset or sandbox environment.
• Demo in UiPath Studio showcasing the integration of human in the loop along with communication mining. This is a must-see use case.
• Q&A Session

Open floor for questions, clarifications, and discussions.

The event will be followed by networking with Tea/coffee and snacks ;)