Size Matters: The Impact of Training Size in Taxonomically-Enriched Word Embeddings

Articles in the same Issue

1. Topical Issue on Type Error Diagnosis and Closely Related Fields
2. A framework for improving error messages in dependently-typed languages
3. A compiler architecture for domain-specific type error diagnosis
4. Type errors for the IDE with Xtext and Xsemantics
5. Topical Issue on Intelligent Methods for Textual Information Retrieval
6. Hypergraph-of-entity
7. Unsupervised and weakly supervised approaches for answer selection tasks with scarce annotations
8. Efficient Hyperparameter Tuning with Grid Search for Text Categorization using kNN Approach with BM25 Similarity
9. Extracting ontological knowledge from Java source code using Hidden Markov Models
10. Modeling concepts and their relationships for corpus-based query auto-completion
11. Research Articles
12. Privacy-aware blockchain for personal data sharing and tracking
13. Bidirectional deep architecture for Arabic speech recognition
14. Feature extraction for license plate location based on L₀-norm smoothing
15. An image processing pipeline to segment iris for unconstrained cow identification system
16. Data analytics to reduce stop-on-fail test in electronics manufacturing
17. Predicting academic success through students’ interaction with Version Control Systems
18. Semi-Supervised learning with Collaborative Bagged Multi-label K-Nearest-Neighbors
19. Size Matters: The Impact of Training Size in Taxonomically-Enriched Word Embeddings
20. Augmenting Neural Machine Translation through Round-Trip Training Approach
21. Task scheduling algorithm based on multi criteria decision making method for cloud computing environment: TSABMCDMCCE
22. Post-Quantum Crystography System for Secure Electronic Voting
23. A review of annotation classification tools in the educational domain
24. Measuring emotions during learning: lack of coherence between automated facial emotion recognition and emotional experience