Andrew Perfors
Home
Research
People
Publications
Teaching
Resources
Blog
CV
Contact
similarity
Predicting human similarity judgments with distributional models: The value of word associations
When do learned transformations influence similarity and categorization?
Predicting human similarity judgments with distributional models: The value of word associations
Finds that semantic networks built from word association data capture similarity judgments better than state-of-the-art corpus models like word2vec.
Structure at every scale: A semantic network account of the similarities between very unrelated concepts
Evidence for widespread thematic structure in the mental lexicon
Strong structure in weak semantic similarity: A graph based account
Cite
×