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In the digital age, the surge in lifelog data presents challenges for traditional search methods due to their reliance on natural language and lack of context. Our research introduces an advanced semantic search application tailored to Lifelog Search Challenge 2024. Leveraging CLIP, BLIP-2, BEIT-3, and all-mpnet-base-v2 models, our system creates precise embeddings from diverse data formats. With Milvus, swift and accurate data retrieval is ensured for efficient indexing. Unique features include metadata enhancement, query standardization, query auto-parsing, effective ranking system, and innovative UI for further lifelog exploration. These advancements redefine lifelog search, offering enhanced access and navigation within archives, and setting a new standard for intelligent, context-aware solutions.
Ho-Le et al. (Mon,) studied this question.