9 citations · 19 across the 3 of their papers we have counts for
3 papers
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…
Parallel Streaming Signature EM-tree: A Clustering Algorithm for Web Scale Applications
Christopher M. de Vries, Lance De Vine, Shlomo Geva +1
The proliferation of the web presents an unsolved problem of automatically analyzing billions of pages of natural language. We introduce a scalable algorithm that clusters hundreds…
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…