Semantic Heat Maps

Explore the Semantic Similarity Heat Map: a tool designed to simplify semantic search in applications by visualizing document relevance through a heat map. This eliminates the need for manual document segmentation, making it easier for developers to integrate advanced search capabilities into their apps.

Demo of the Semantic Similarity Heat Map

Demo of the Semantic Similarity Heat Map

Join our beta program for an exclusive early access to the Semantic Search Heat Map API! Simply email us at beta-semantic-heatmap@zoplabs.com with the subject line ‘Beta Access Request’.

How It Works

The Semantic Search Heat Map uses embedding model outputs to assign a relevance value to each token in a document. High-value areas indicate relevance to the search query, removing the need to segment documents manually. This method is straightforward and aims to improve search result accuracy.

Importance in Development

Semantic search aims to understand the intent behind queries. The Heat Map enhances this by indicating which parts of a document are most relevant to a query, making it a practical tool for developers to improve search functionality in their applications. It’s compatible with existing embedding models, facilitating integration without extensive development overhead.

Use Cases

  • Educational Content: Helps users navigate through large documents to find relevant sections.
  • Legal Documents: Simplifies finding specific information in complex legal texts.
  • Content Management: Improves content discovery in digital platforms.
  • Research: Aids in locating precise information within large datasets.

Integration

  1. API Key: Get an API key to connect your application with the Semantic Search Heat Map API.
  2. Model Training: Train the heat map using outputs from your embedding model to suit your application’s needs.
  3. Search Improvement: Use the heat map to guide users to relevant document sections effortlessly.

For code examples and more detailed integration information, refer to our developer documentation.

Summary

The Semantic Search Heat Map is a straightforward, developer-focused tool aiming to enhance application search functionality by visualizing document relevance. By simplifying the integration of semantic search capabilities and removing the need for manual document segmentation, it seeks to make developers’ work more efficient and user searches more effective. Join our beta program to contribute to its development and start integrating this tool into your projects.


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