Cognitive Personalized Search Integrating Large Language Models with an Efficient Memory Mechanism
Yujia Zhou,
Qiannan Zhu,
Jiajie Jin
et al.
Abstract:Traditional search engines usually provide identical search results for all users, overlooking individual preferences. To counter this limitation, personalized search has been developed to re-rank results based on user preferences derived from query logs. Deep learningbased personalized search methods have shown promise, but they rely heavily on abundant training data, making them susceptible to data sparsity challenges. This paper proposes a Cognitive Personalized Search (CoPS) model, which integrates Large L… Show more
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