arXiv:1606.07736cs.CL
Issues in evaluating semantic spaces using word analogies
Early discovery. Linked by one identifiable commenter. This paper is outside the main ranking; a mention is not an endorsement.
Abstract
The offset method for solving word analogies has become a standard evaluation tool for vector-space semantic models: it is considered desirable for a space to represent semantic relations as consistent vector offsets. We show that the method's reliance on cosine similarity conflates offset consistency with largely irrelevant neighborhood structure, and propose simple baselines that should be used to improve the utility of the method in vector space evaluation.
I learned about them just a few days before publishing this post (and I link to the second one, in the "technicalities" section). Though, some statements about analogies should be taken with a grain of salt, see: Tal Linzen, Issues in evaluating semantic spaces using word…
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I address this point. For scalar product, well, these word vectors are defined such that their scalar product approximate the pointwise mutual information between a pair of words (or sometimes other quantity, depending on the actual algorithm). For differences - see this…
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