Technical comparison of semantic search with traditional search
EchoMemo's search paradigm revolutionizes in three dimensions:
- Search Dimension Breakthrough: While traditional approaches rely on keyword matching of title/description text, EchoMemo can retrieve unstructured information such as video frames, graphic elements, spoken descriptions, etc.
- Increased search accuracy: On the social media content test set, for the query "red costume dance video", the accuracy of CV-based semantic search reaches 921 TP3T, far exceeding the 581 TP3T of traditional text search.
- Fuzzy search capability: Supports relevance queries such as "similar to a previously saved video of a tech conference", and realizes conceptual retrieval by embedding vector similarity computation.
In terms of technical implementation, the system adopts the multimodal model architecture of BERT+CLIP, and uses more than 5 million sets of social media content data for fine-tuning during training. Cross-language embedding alignment is optimized for Chinese search to ensure that Chinese descriptions can accurately match multilingual content.
This answer comes from the articleEcho Memo: a bookmarking tool that uses AI to understand and search social media contentThe
May not be reproduced without permission:AI productivity tools " EchoMemo's semantic search technology has significant advantages over traditional keyword searches
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