Towards Generalizeable Semantic Product Search by Text Similarity Pre-training on Search Click Logs
Recently, semantic search has been successfully applied to E-commerce product search and the learned semantic space for query and product encoding are expected to generalize well to unseen queries or products. Yet, whether generalization can conveniently emerge has not been thoroughly studied in the domain thus far. In this paper, we examine several general-domain and domain-specific pre-trained Roberta variants and discover that general-domain fine-tuning does not really help generalization which aligns with the discovery of prior art, yet proper domain-specific fine-tuning with clickstream data can lead to better model generalization, based on a bucketed analysis of a manually annotated query-product relevance data.
Code (0)
등록된 구현이 없습니다.
Tasks
text similaritySimilar Papers 제목 키워드 기반
Efficient Embedding of Semantic Similarity in Control Policies via Entangled Bisimulation
Learning generalizeable policies from visual input in the presence of visual distractions is a challenging problem in reinforcement learning. Recently, there has been renewed interest in bisimulation metrics as a tool to…
Data AugmentationReinforcement Learning (RL)Semantic SimilaritySemantic Textual SimilarityTowards Generalizable Semantic Product Search by Text Similarity Pre-training on Search Click Logs
Recently, semantic search has been successfully applied to e-commerce product search and the learned semantic space(s) for query and product encoding are expected to generalize to unseen queries or products. Yet, whether…
text similarityVisual Fashion-Product Search at SK Planet
We build a large-scale visual search system which finds similar product images given a fashion item. Defining similarity among arbitrary fashion-products is still remains a challenging problem, even there is no exact gro…
Semantic SimilaritySemantic Textual SimilarityImproving Relevance Quality in Product Search using High-Precision Query-Product Semantic Similarity
Ensuring relevance quality in product search is a critical task as it impacts the customer’s ability to find intended products in the short-term as well as the general perception and trust of the e-commerce system in the…
Re-RankingSemantic SimilaritySemantic Textual SimilarityBeyond Cosine Similarity
Cosine similarity, the standard metric for measuring semantic similarity in vector spaces, is mathematically grounded in the Cauchy-Schwarz inequality, which inherently limits it to capturing linear relationships--a cons…
Semantic Textual SimilaritySemantic Similarity