Name
Abstract | ||
|---|---|---|
This paper presents results of our experiments for the next utterance ranking on the Ubuntu Dialog Corpus -- the largest publicly available multi-turn dialog corpus. First, we use an in-house implementation of previously reported models to do an independent evaluation using the same data. Second, we evaluate the performances of various LSTMs, Bi-LSTMs and CNNs on the dataset. Third, we create an ensemble by averaging predictions of multiple models. The ensemble further improves the performance and it achieves a state-of-the-art result for the next utterance ranking on this dataset. Finally, we discuss our future plans using this corpus. |
Year | Venue | Field |
|---|---|---|
2015 | CoRR | Dialog box,Ranking,Computer science,Baseline (configuration management),Utterance,Natural language processing,Artificial intelligence,Deep learning,Machine learning,Multiple Models |
DocType | Volume | Citations |
Journal | abs/1510.03753 | 23 |
PageRank | References | Authors |
0.87 | 10 | 3 |
Name | Order | Citations | PageRank |
|---|---|---|---|
| Rudolf Kadlec | 1 | 229 | 16.25 |
| martin schmid | 2 | 30 | 4.11 |
| Jan Kleindienst | 3 | 220 | 23.74 |