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SBE
A sentence similarity model optimized for Russian e-commerce search queries, specifically designed for differentiating product search queries
Downloads 15
Release Time : 9/28/2024
Model Overview
This model is based on the Transformer architecture, optimized for short text search queries in the Russian e-commerce domain, capable of accurately calculating semantic similarity between queries to help differentiate different products
Model Features
Russian e-commerce optimization
Specifically trained and optimized for Russian e-commerce search queries
Large-scale training data
Trained using a corpus containing 269 million Russian search queries
High-precision validation
Validation dataset includes 362,000 manually annotated instances
Short text optimization
Specially optimized for semantic understanding of short text search queries
Model Capabilities
Calculate sentence similarity
E-commerce product differentiation
Russian semantic understanding
Short text encoding
Use Cases
E-commerce search
Product query matching
Identify search queries with different expressions but referring to the same product
cos( SBE("apple 16 blue pro max 256"), SBE("iphone 16 blue pro max 256") ) = 0.96
Product version differentiation
Differentiate queries for different product versions
cos( SBE("iphone 15 pro max"), SBE("iphone 16 pro max") ) = 0.85
Multilingual matching
Cross-language product matching
Identify the same product expressed in different languages
cos( SBE("iphone 15 pro max"), SBE("苹果15 pro max") ) = 0.98
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