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This paper constructs the tree knowledge graph from Vietnamese high school History textbooks to produce 750 nodes and 4,341 semantic edges with controlled ontology growth from 40 to 41 types.
Large language models can improve recommendation quality by reasoning explicitly over user history and candidate items - for example, extracting a user's preferences or explaining why one item fits better than another - rather than mapping history directly to a ranked list. This reasoning, however, is expensive to repe...
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