Paper: Formalizing Word Sampling for Vocabulary Prediction as Graph-based Active Learning

ACL ID D14-1143
Title Formalizing Word Sampling for Vocabulary Prediction as Graph-based Active Learning
Venue Conference on Empirical Methods in Natural Language Processing
Session Main Conference
Year 2014
Authors

Predicting vocabulary of second language learners is essential to support their lan- guage learning; however, because of the large size of language vocabularies, we cannot collect information on the entire vocabulary. For practical measurements, we need to sample a small portion of words from the entire vocabulary and pre- dict the rest of the words. In this study, we propose a novel framework for this sam- pling method. Current methods rely on simple heuristic techniques involving in- flexible manual tuning by educational ex- perts. We formalize these heuristic tech- niques as a graph-based non-interactive active learning method as applied to a spe- cial graph. We show that by extending the graph, we can support additional function- ality such as incorporating domain speci- ficity and sam...