Learning systems of concepts with an infinite relational model
作者： Thomas L. Griffiths , Naonori Ueda , Joshua B. Tenenbaum , Takeshi Yamada , Charles Kemp
DOI:
关键词: Relational model 、 Artificial intelligence 、 Ontology (information science) 、 Cluster analysis 、 Semantic memory 、 Computer science 、 Structure (mathematical logic) 、 Kinship 、 Set (abstract data type)
摘要: Relationships between concepts account for a large proportion of semantic knowledge. We present nonparametric Bayesian model that discovers systems related concepts. Given data involving several sets entities, our the kinds entities in each set and relations are possible or likely. apply approach to four problems: clustering objects features, learning ontologies, discovering kinship systems, structure political data.
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