Name
Abstract | ||
|---|---|---|
Most community question answering (CQA) websites manage plenty of question-answer pairs (QAPs) through topic-based organizations, which may not satisfy users' fine-grained search demands. Facets of topics serve as a powerful tool to navigate, refine, and group the QAPs. In this work, we propose FACM, a model to annotate QAPs with facets by extending convolution neural networks (CNNs) with a matchi... |
Year | DOI | Venue |
|---|---|---|
2018 | 10.1162/neco_a_01077 | Neural Computation |
Field | DocType | Volume |
Kernel (linear algebra),Data set,Question answering,Annotation,Convolution,Phrase,Facet (geometry),Artificial intelligence,Artificial neural network,Mathematics,Machine learning | Journal | 30 |
Issue | ISSN | Citations |
6 | 0899-7667 | 0 |
PageRank | References | Authors |
0.34 | 19 | 6 |
Name | Order | Citations | PageRank |
|---|---|---|---|
| Bei Wu | 1 | 11 | 4.27 |
| Bifan Wei | 2 | 38 | 6.39 |
| Jun Liu | 3 | 10 | 4.54 |
| Zhaotong Guo | 4 | 0 | 0.34 |
| Yuanhao Zheng | 5 | 0 | 0.68 |
| Yihe Chen | 6 | 3 | 2.06 |