Opensearch Semantic Highlighter V1
The OpenSearch Semantic Highlighter is a text classifier designed to evaluate the relevance of document sentences to queries.
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Release Time : 4/22/2025
Model Overview
This model takes a document and a query as input and returns a binary score for each sentence in the document indicating its relevance to the query, making it suitable for semantic search and highlighting scenarios.
Model Features
Semantic Relevance Assessment
Accurately assesses the semantic relevance of each sentence in a document to the query
Highlighting Support
Optimized for search result highlighting scenarios
BERT Architecture
Based on BERT architecture, with strong semantic understanding capabilities
Model Capabilities
Semantic Relevance Scoring
Text Classification
Search Result Highlighting
Use Cases
Information Retrieval
Search Engine Result Highlighting
Highlight the most relevant document fragments in search engine results
Improves the readability and user experience of search results
Document Summary Generation
Automatically generate document summaries based on queries
Quickly locate the most relevant parts of a document in relation to the query
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