Name
Abstract | ||
|---|---|---|
Dense word embeddings, which encode meanings of words to low-dimensional vector spaces, have become very popular in natural language processing (NLP) research due to their state-of-the-art performances in many NLP tasks. Word embeddings are substantially successful in capturing semantic relations among words, so a meaningful semantic structure must be present in the respective vector spaces. Howev... |
Year | DOI | Venue |
|---|---|---|
2018 | 10.1109/TASLP.2018.2837384 | IEEE/ACM Transactions on Audio, Speech, and Language Processing |
Keywords | DocType | Volume |
Semantics,Task analysis,Natural language processing,Standards,Speech processing,Sparse matrices,Statistical analysis | Journal | 26 |
Issue | ISSN | Citations |
10 | 2329-9290 | 6 |
PageRank | References | Authors |
0.43 | 15 | 5 |
Name | Order | Citations | PageRank |
|---|---|---|---|
| Lutfi Kerem Senel | 1 | 6 | 1.11 |
| Ihsan Utlu | 2 | 6 | 1.45 |
| Veysel Yücesoy | 3 | 6 | 1.45 |
| Aykut Koc | 4 | 12 | 9.01 |
| Tolga Çukur | 5 | 36 | 8.84 |