Papers by Daniel Gillblad
Streaming word similarity mining on the cheap (D18-1)
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| Challenge: | Existing methods to estimate word similarities are to embed words in vector space and then calculate similarities between corresponding vectors. |
| Approach: | They propose a method that explicitly counts second-order co-occurrences to estimate word similarities from streams. |
| Outcome: | The proposed method is scalable, converges rapidly, behaves robustly under parameter changes, and captures word similarities on par with state-of-the-art word embeddings. |