Name
Abstract | ||
|---|---|---|
Readitopics provides a new tool for browsing a textual corpus that showcases several recent work for labeling topic models and estimating topic coherence. We will demonstrate the potential of these techniques to get a deeper understanding of the topics that structure different kinds of datasets. This tool is provided as a Web demo but it can be easily installed to experiment with your own dataset. It can be further extended to deal with more advanced topic modeling techniques. |
Year | DOI | Venue |
|---|---|---|
2018 | 10.24963/ijcai.2018/867 | IJCAI |
Field | DocType | Citations |
Information retrieval,Computer science,Coherence (physics),Artificial intelligence,Topic model,Machine learning | Conference | 0 |
PageRank | References | Authors |
0.34 | 0 | 6 |
Name | Order | Citations | PageRank |
|---|---|---|---|
| Julien Velcin | 1 | 161 | 27.83 |
| Antoine Gourru | 2 | 1 | 2.38 |
| Erwan Giry-Fouquet | 3 | 0 | 0.34 |
| Christophe Gravier | 4 | 159 | 34.49 |
| Mathieu Roche | 5 | 222 | 39.78 |
| Pascal Poncelet | 6 | 768 | 126.47 |