《Proactive Human-Machine Conversation with Explicit Conversation Goals》
論文出處：ACL 2019 1. 摘要 論文提出了一種基於知識圖譜能主導對話的對話系統，並開源了對應的數據集DuConv。該數據集涉及電影、導演和演員相關題材，包含3w個多輪對話，約27w個句子。每個對話包含一個目標三元組[START, TOPIC_A, TOPIC_B]，表示系統的目標是將對話主題從A引導到B；另外包括一系列跟TOPIC_A或者TOPIC_B有關的知識三元組，形式爲（主體，謂詞，
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相關文章
- 1. short text conversation: retrieval
- 2. 001_A private conversation
- 3. English conversation example in interview
- 4. short text conversation: neural network
- 5. Lesson 10 Telephone Conversation 2
- 6. Leeson 11 Telephone Conversation 3
- 7. 【ICJAI2018】Commonsense Knowledge Aware Conversation Generation with Graph Attention
- 8. LeetCode打卡（五）ZigZag Conversation
- 9. A Knowledge-Grounded Neural Conversation Model
- 10. lijiwei2-A Persona-Based Neural Conversation Model