A copy of this work was available on the public web and has been preserved in the Wayback Machine. The capture dates from 2022; you can also visit the original URL.
The file type is application/pdf
.
A Comprehensive Analysis of PMI-based Models for Measuring Semantic Differences
2021
Pacific Asia Conference on Language, Information and Computation
The task of detecting words with semantic differences across corpora is mainly addressed by word representations such as word2vec or BERT. However, in the real world where linguists and sociologists apply these techniques, computational resources are typically limited. In this paper, we extend an existing simultaneously optimized model that can be trained on CPU to perform this task. Experimental results show that the extended models achieved comparable or superior results to strong baselines
dblp:conf/paclic/AidaKOTM21
fatcat:qecopkctzvbpbkbsqeuoa47rya