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Intro
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UNSILO Mission
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UNSILO Core Technology
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Key Challenges
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Full Text Search
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Using Keywords and Ontologies
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UNSILO Exhaustive Concept Extraction
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UNSILO Complete Semantic Mapping
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Phrase Extraction
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Word Embeddings and Word2Vec
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Ontology Augmented Vector-space
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Synsets built from Vector Cosine Similarity
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Human readable Fingerprints
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UNSILO Discovery Widgets
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Easier Content Exploration
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Future Directions
Description:
Save Big on Coursera Plus. 7,000+ courses at $160 off. Limited Time Only! Grab it 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.

Discovering Research Ideas Using Semantic Vectors and Machine Learning

GOTO Conferences
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