2017emnlp-Author-aware Aspect Topic Sentiment Model to Retrieve Supporting Opinions from Reviews閱讀筆記
這個感覺比較有用的是結合了語境的信息 Abstract 用戶關於產品的評論是非常多樣化甚至自相矛盾的，這就造成了用戶難以確認一條評論是否可信。我們研究了在評論中尋找支持觀點的問題，我們提出了一個SURF的架構，這個架構首先識別在評論中的觀點表達，然後在其他的評論中發現相似的觀點。我們設計了一種新的概率圖形模型, 它將觀點作爲一個由主題和情緒維度的組合構成的aspect來捕獲, 同時考慮到個別
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相關文章
- 1. JST ：Joint sentiment topic model & ASUM ：Aspect sentiment unification model
- 2. Recurrent Attention Network on Memory for Aspect Sentiment 閱讀筆記
- 3. 《A Joint Model of Term Exaction and Polarity Classification for Aspect-based Sentiment Analysis》閱讀筆記
- 4. 【論文閱讀筆記】Modeling Sentiment Dependencies with Graph Convolutional Networks for Aspect-level Sentiment
- 5. Aspect Based Sentiment Analysis with Gated Convolutional Networks 閱讀筆記
- 6. 2017emnlp---Document-Level Multi-Aspect Sentiment Classification as Machine Comprehension閱讀筆記
- 7. 《Attention-based LSTM for Aspect-level Sentiment Classification》閱讀筆記
- 8. acl2018---Aspect Based Sentiment Analysis with Gated Convolutional Networks論文閱讀筆記
- 9. IJCNLP2015-Weakly Supervised Models of Aspect-Sentiment for Online Course Discussion Forums閱讀筆記
- 10. Dependency Graph Enhanced Dual-transformer Structure for Aspect-based Sentiment Classification閱讀筆記