Short answer
A well-built Semantic Map helps AskTuring understand the key terms, related phrases, and alternative wording used in your Index, making searches faster and results more precise. It uses AskTuring’s patented technology to improve both search and understanding.
Full explanation
The Semantic Map is a curated list of important terms and their alternative phrases that exist in your documents. By defining these terms for a specific Index, you give AskTuring the context it needs to recognize that different words or phrases may refer to the same concept.
AskTuring’s patented semantic mapping technology strengthens this process by creating deeper connections between related concepts, ensuring that searches return the most relevant information—even when different wording is used.
For example, if “performance review” appears in your documents but users might also search for “employee evaluation,” adding both to the Semantic Map as related terms ensures the system makes the connection.
Optimizing for faster, more precise understanding means:
Reducing the chance of missing relevant results because of different wording.
Improving query relevance for both technical and non-technical users.
Strengthening the AI’s ability to connect related concepts within your Index.
Why it matters
Semantic mapping works hand-in-hand with AskTuring’s Retrieval-Augmented Generation (RAG) process to further reduce irrelevant results and hallucinations. By giving the AI a stronger understanding of how your terms are connected, you make it more likely that answers will be complete, accurate, and grounded in your documents.
Tips
Review your Index for specialized terms and common synonyms.
Add both the main term and all likely alternative terms.
Update the Semantic Map when new terms or acronyms appear in your documents.