Incorporating Word Correlation Knowledge into Topic Modeling
開始沒有仔細看的時候，也不懂MRF的應用，學習細節才知道重點。 論文 簡單描述MRF-LDA的場景：首先，假設話題的粉筆θ，以及單詞分佈β都服從狄利克雷分佈，每個單詞具有話題標籤z。提取單詞的關聯關係，主要是語義的相似性，用來學習話題的一致性。所以用到了MRF，在潛在話題層。給定文檔d和N單詞，判斷單詞對（根據外部知識）創建無向邊連接他們的話題標籤，獲取圖G和單詞標籤。如下圖的5個節點，4條邊(z
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相關文章
- 1. Incorporating Unstructured Textual Knowledge Sources into Neural
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- 10. 論文筆記《DermaKNet: Incorporating the knowledge of dermatologists to Convolutional Neural Networks for 》