Energy — User Intent Classification for Enhanced System Interaction

Overview

The User Intent Classification DAG is designed to improve user interactions within energy sector enterprise systems by leveraging advanced classification models. The primary purpose of this DAG is to analyze user queries and accurately classify their intents, thereby guiding users toward relevant resources and enhancing their experience in business portals. The data ingestion process begins with collecting user interaction logs, which serve as the foundational input data. These logs include sear

The User Intent Classification DAG is designed to improve user interactions within energy sector enterprise systems by leveraging advanced classification models. The primary purpose of this DAG is to analyze user queries and accurately classify their intents, thereby guiding users toward relevant resources and enhancing their experience in business portals. The data ingestion process begins with collecting user interaction logs, which serve as the foundational input data. These logs include search queries, navigation paths, and interaction timestamps, providing a comprehensive view of user behavior. Once ingested, the data undergoes a series of processing steps. First, the data is cleaned and pre-processed to remove any noise and irrelevant information. Next, natural language processing techniques are applied to extract meaningful features from the user queries. Following this, the classification model is trained on historical interaction data to identify patterns and classify user intents accurately. The model outputs a set of classified intents, which are then validated through quality control measures to ensure accuracy and reliability. The final outputs of the DAG include categorized user intents and recommendations for resource allocation, which are invaluable for improving user satisfaction and operational efficiency. Monitoring KPIs such as classification accuracy, user engagement rates, and resource utilization help assess the effectiveness of the DAG. Ultimately, this DAG delivers significant business value by enhancing user experience, reducing support costs, and improving resource allocation within the energy sector.

Part of the Governance & Compliance solution for the Energy industry.

Use cases

• Enhances user experience through targeted resource recommendations
• Reduces operational costs by optimizing support resources
• Improves efficiency in user navigation within business portals
• Increases user satisfaction through accurate intent classification
• Facilitates better compliance with governance requirements