9 citations · 10 across the 2 of their papers we have counts for
2 papers
cs.CL2016★ 9 cited
The Benefits of Word Embeddings Features for Active Learning in Clinical Information Extraction
Mahnoosh Kholghi, Lance De Vine, Laurianne Sitbon +2
This study investigates the use of unsupervised word embeddings and sequence features for sample representation in an active learning framework built to extract clinical concepts f…
cs.IR2010★ 1 cited
Random Indexing K-tree
Christopher M. De Vries, Lance De Vine, Shlomo Geva
Random Indexing (RI) K-tree is the combination of two algorithms for clustering. Many large scale problems exist in document clustering. RI K-tree scales well with large inputs due…