Name
Abstract | ||
|---|---|---|
As an important step of human-computer interaction, conversion generation has attracted much attention and has a rising tendency in recent years. This paper gives a detailed description about an ensemble system for short text conversation generation. The proposed system consists of four subsystems, a quick response candidates selecting module, an information retrieval system, a generation-based system and an ensemble module. An advantage of this system is that multiple versions of generated responses are taken into account resulting a more reliable output. In the NLPCC 2017 shared task "Emotional Conversation Generation Challenge", the ensemble system generates appropriate responses for Chinese SNS posts and ranks at the top of participant list. |
Year | DOI | Venue |
|---|---|---|
2017 | 10.1007/978-3-319-73618-1_5 | Lecture Notes in Artificial Intelligence |
DocType | Volume | ISSN |
Conference | 10619 | 0302-9743 |
Citations | PageRank | References |
0 | 0.34 | 0 |
Authors | ||
5 | ||
Name | Order | Citations | PageRank |
|---|---|---|---|
| Yimeng Zhuang | 1 | 0 | 0.68 |
| Xianliang Wang | 2 | 0 | 0.34 |
| Han Zhang | 3 | 123 | 28.55 |
| Jinghui Xie | 4 | 0 | 0.68 |
| Xuan Zhu | 5 | 12 | 0.95 |