High Tech — Hybrid Document Indexing for Semantic Search

Overview

The purpose of this DAG is to implement a hybrid indexing system that leverages both BM25 and vector-based methodologies to improve the efficiency and accuracy of semantic searches within high-tech literature. The data sources include newly added documents that trigger the indexing process. The ingestion pipeline begins with text extraction from these documents, followed by the creation of an index that incorporates both traditional and modern indexing techniques. During this process, synonym up

The purpose of this DAG is to implement a hybrid indexing system that leverages both BM25 and vector-based methodologies to improve the efficiency and accuracy of semantic searches within high-tech literature. The data sources include newly added documents that trigger the indexing process. The ingestion pipeline begins with text extraction from these documents, followed by the creation of an index that incorporates both traditional and modern indexing techniques. During this process, synonym updates are performed to enhance the searchability of terms, ensuring that the index remains relevant and comprehensive. Quality control measures are integrated at various stages to validate data integrity and ensure the reliability of the outputs. The final outputs are accessible through a user-friendly semantic search interface, allowing users to retrieve information quickly and efficiently. Key performance indicators (KPIs) for monitoring include response time and the relevance of search results, which are crucial for assessing the effectiveness of the indexing process. The business value lies in enabling high-tech organizations to streamline their literature reviews, enhance knowledge discovery, and ultimately support informed decision-making through improved access to critical information.

Part of the Literature Review solution for the High Tech industry.

Use cases

• Improved information retrieval speeds for high-tech research
• Enhanced accuracy in search results through hybrid methods
• Streamlined literature reviews for faster decision-making
• Increased user satisfaction with relevant search outputs
• Scalable indexing solution accommodating growing document volumes