“Each sentence of OMCS was entered by a goal-directed user hoping to contribute common sense, resulting in a wealth of statements that focus on simple, real-world concepts that often go unstated.”Tagged: Open Mind Common Sense, Goal-Directed Learning, ConceptNet, Artificial intelligence, QC-Learning
“Normalization inherently involves discarding information, but since ConceptNet 3, we have ensured that this information is stored with the assertion and not truly discarded”Tagged: ConceptNet, Data Normalization, Machine Learning, No Data Left Behind
“ConceptNet includes not just definitions and lexical relationships, but also the common-sense associations that ordinary people make among these concepts. Its sources range in formality from dictionaries to online games.”Tagged: ConceptNet, Mapping Langauge, Machine Learning
“Word embeddings or word vectors are a way for computers to understand what words mean in text written by people. The goal is to represent words as lists of numbers, where small changes to the numbers represent small changes to the meaning of the word. This is a technique that helps in building AI…”Tagged: Word Vectors, NLP, Artificial intelligence, Word Abstractions