Consumer Products — Ontology Development for Document Classification and Search Enhancement

Overview

The primary purpose of this DAG is to create and maintain an ontology that improves the searchability and classification of documents within the consumer products sector. It ingests data from various sources, including internal document repositories, user feedback forms, and market research reports. The ingestion pipeline processes these inputs to identify key concepts and their relationships, which are essential for constructing a robust ontology. The processing steps include data cleansing to

The primary purpose of this DAG is to create and maintain an ontology that improves the searchability and classification of documents within the consumer products sector. It ingests data from various sources, including internal document repositories, user feedback forms, and market research reports. The ingestion pipeline processes these inputs to identify key concepts and their relationships, which are essential for constructing a robust ontology. The processing steps include data cleansing to ensure quality, concept extraction to highlight relevant themes, relationship mapping to establish connections between concepts, and ontology construction to formalize the knowledge structure. Regular updates are integrated into the workflow to reflect changes in market trends and user requirements, ensuring that the ontology remains current and relevant. Outputs include a user-accessible ontology portal, updated documentation, and a report on key insights derived from the analysis. Monitoring key performance indicators (KPIs) such as user engagement metrics, search efficiency, and document retrieval accuracy helps assess the effectiveness of the ontology. Ultimately, this DAG delivers significant business value by enhancing information retrieval processes, improving user satisfaction, and supporting informed decision-making in the consumer products industry.

Part of the Literature Review solution for the Consumer Products industry.

Use cases

• Improves document retrieval speed and accuracy
• Enhances user satisfaction through better search results
• Facilitates informed decision-making with relevant insights
• Enables agile responses to market changes
• Reduces time spent on document classification tasks