PolyUCOMP: Combining Semantic Vectors with Skip bigrams for Semantic Textual Similarity

PolyUCOMP-CORE\_TYPED: Computing Semantic Textual Similarity using Overlapped Senses

Using Skipgrams, Bigrams, and Part of Speech Features for Sentiment Classification of Twitter Messages

Semantics- and Syntax-related Subvectors in the Skip-gram Embeddings

We show that the skip-gram embedding of any word can be decomposed into two subvectors which roughly correspond to semantic and syntactic roles of the word.

Skip-Thought Memory Networks

Question Answering (QA) is fundamental to natural language processing in that most nlp problems can be phrased as QA (Kumar et al., 2015). Current weakly supervised memory network models that have been proposed so far st…

The MeSH-gram Neural Network Model: Extending Word Embedding Vectors with MeSH Concepts for UMLS Semantic Similarity and Relatedness in the Biomedical Domain

Eliciting semantic similarity between concepts in the biomedical domain remains a challenging task. Recent approaches founded on embedding vectors have gained in popularity as they risen to efficiently capture semantic r…