Cross-domain Sentiment Classification using Sentiment Sensitive Embeddings
- Submitting institution
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The University of Liverpool
- Unit of assessment
- 11 - Computer Science and Informatics
- Output identifier
- 12003
- Type
- D - Journal article
- DOI
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10.1109/TKDE.2015.2475761
- Title of journal
- IEEE Transactions on Knowledge and Data Engineering
- Article number
- 2
- First page
- 389
- Volume
- 28
- Issue
- 02
- ISSN
- 1041-4347
- Open access status
- Out of scope for open access requirements
- Month of publication
- September
- Year of publication
- 2015
- URL
-
-
- Supplementary information
-
-
- Request cross-referral to
- -
- Output has been delayed by COVID-19
- No
- COVID-19 affected output statement
- -
- Forensic science
- No
- Criminology
- No
- Interdisciplinary
- No
- Number of additional authors
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2
- Research group(s)
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-
- Citation count
- 49
- Proposed double-weighted
- No
- Reserve for an output with double weighting
- No
- Additional information
- This journal version extends the ACL'14 conference paper “Learning to Predict Distributions of Words across Domains”. The results presented in this paper contributed to the award of a prestigious Amazon Scholarship to Bollegala. This research has inspired follow up work on domain adaptation such as domain-sensitive word embedding learning by Shi et al (ACL 2018) and multilingual sentiment classification by Xu and Wan (EMNLP 2017).
- Author contribution statement
- -
- Non-English
- No
- English abstract
- -