現在，您應該已更加瞭解如何：
- 說明推薦系統的用途。
- 瞭解建議工具系統的元件，包括 生成候選字詞、評分及重新排名。
- 使用嵌入來表示項目和查詢。
- 深入瞭解常見技術的技術知識 用於生成候選文字。
除非另有註明，否則本頁面中的內容是採用創用 CC 姓名標示 4.0 授權，程式碼範例則為阿帕契 2.0 授權。詳情請參閱《Google Developers 網站政策》。Java 是 Oracle 和/或其關聯企業的註冊商標。
上次更新時間：2024-08-13 (世界標準時間)。
[null,null,["上次更新時間：2024-08-13 (世界標準時間)。"],[[["Recommendation systems predict which items a user will like based on their past behavior and preferences."],["These systems use a multi-stage process: identifying potential items (candidate generation), evaluating their relevance (scoring), and refining the order of presentation (re-ranking)."],["Embeddings play a key role in representing items and user queries, facilitating comparisons for recommendations."],["Two primary approaches for recommendation are content-based filtering (using item features) and collaborative filtering (using user similarities)."],["Deep learning techniques enhance traditional methods like matrix factorization, enabling more complex and accurate recommendations."]]],[]]