Discovering Research Ideas Using Semantic Vectors and Machine Learning

Explore how semantic vectors and machine learning can be used to discover research ideas in this 49-minute conference talk from GOTO Copenhagen 2016. Learn about UNSILO's mission to enrich scientific content and improve discoverability across domains. Dive into key challenges in full-text search, keyword usage, and ontologies. Discover UNSILO's innovative approaches, including exhaustive concept extraction, complete semantic mapping, and phrase extraction. Understand the application of word embeddings, Word2Vec, and ontology-augmented vector spaces. Explore how synsets are built using vector cosine similarity and how human-readable fingerprints are created. See demonstrations of UNSILO's discovery widgets for easier content exploration. Gain insights into future directions for research idea discovery and content enrichment in scientific publishing.