Publication | Open Access
SimCompass: Using Deep Learning Word Embeddings to Assess Cross-level Similarity
32
Citations
26
References
2014
Year
Unknown Venue
Meta-learning (Computer Science)EngineeringMachine LearningMeta-learningDeep Learning ParadigmsCorpus LinguisticsLanguage ProcessingText MiningWord EmbeddingsNatural Language ProcessingData ScienceComputational LinguisticsCross-level SimilarityMulti-task LearningLanguage StudiesKnowledge DiscoveryDeep LearningDistributional SemanticsSemeval-2014 Task 3Domain Knowledge ModelingMeta-learning FrameworkLinguisticsSemantic Similarity
This article presents our team’s participating system at SemEval-2014 Task 3. Using a meta-learning framework, we experiment with traditional knowledgebased metrics, as well as novel corpusbased measures based on deep learning paradigms, paired with varying degrees of context expansion. The framework enabled us to reach the highest overall performance among all competing systems.
| Year | Citations | |
|---|---|---|
Page 1
Page 1