Making use of latent semantic analysis, we explore the hypothesis that local linguistic context can serve to identify multi-word expressions that have noncompositional meanings. We propose that vector-similarity between distribution vectors associated with an MWE as a whole and those associated with its constitutent parts can serve as a good measure of the degree to which the MWE is compositional. We present experiments that show that low (cosine) similarity does, in fact, correlate with non-compositionality.
REF make use of latent semantic analysis (LSA) to explore the local linguistic context that can serve to identify multiword expressions that have non-compositional meaning.
Automatic Identification Of Non-Compositional Multi-Word Expressions Using Latent Semantic Analysis
Workshop On Multiword Expressions: Identifying And Exploiting Underlying Properties
Mathematics