Papers with unsupervised topic models

2 papers
Know thy Corpus! Robust Methods for Digital Curation of Web corpora (2020.lrec-1)

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Challenge: Existing methods for estimating the lexicon of Web corpora have not been used to train pre-trained models.
Approach: They propose a framework for digital curation of Web corpora to provide robust estimation of their parameters.
Outcome: The proposed framework provides robust estimation of Web corpora's composition and lexicon . the proposed framework is similar to the BNC and ELMO models, but lacks curated categories .
Leveraging Just a Few Keywords for Fine-Grained Aspect Detection Through Weakly Supervised Co-Training (D19-1)

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Challenge: Current weakly supervised approaches for learning aspect classifiers require many fine-grained aspect labels, which are labor-intensive to obtain.
Approach: They propose a weakly supervised approach that leverages seed words for aspect detection . they propose supervised student-teacher approach that uses teacher to train student models .
Outcome: The proposed approach outperforms previous weakly supervised approaches by 14.1 F1 points on average in six domains of product reviews and six multilingual datasets of restaurant reviews.

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