What is Done is Done: an Incremental Approach to Semantic Shift Detection
Contextual word embedding techniques for semantic shift detection are receiving more and more attention. In this paper, we present What is Done is Done (WiDiD), an incremental approach to semantic shift detection based on incremental clustering techniques and contextual embedding methods to capture the changes over the meanings of a target word along a diachronic corpus. In WiDiD, the word contexts observed in the past are consolidated as a set of clusters that constitute the “memory” of the word meanings observed so far. Such a memory is exploited as a basis for subsequent word observations, so that the meanings observed in the present are stratified over the past ones.
PDF AbstractTasks
Datasets
Add Datasets
introduced or used in this paper
Results from the Paper
Submit
results from this paper
to get state-of-the-art GitHub badges and help the
community compare results to other papers.
Methods
No methods listed for this paper. Add
relevant methods here
