JST ：Joint sentiment topic model & ASUM ：Aspect sentiment unification model
Joint sentiment /topic model JST模型從文本檢測情感和主題 之前的工作缺點：基於機器學習的情感分類需要大量的人工標記； 一個領域訓練的情感分類模型不能很好地應用於另一個領域； 主題/特徵檢測和情感分類經常分開來進行，忽略了它們的相互依賴性。 JST 同時建模話題和情感 情感分析可以分爲三類：積極，消極和neutral。更細粒度的可以分析單個用戶對特定item和話
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相關文章
- 1. 《A Joint Model of Term Exaction and Polarity Classification for Aspect-based Sentiment Analysis》閱讀筆記
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