Deceptive reviews detection has attract- ed significant attention from both business and research communities. However, due.
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Jan 19, 2024 · Identifying deceptive reviews has important theoretical meaning and practical value. While previous works focus on some heuristic rules or ...
[PDF] Positive Unlabeled Learning for Deceptive Reviews Detection ...
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A semi-supervised model, called mixing population and individual property PU learning (MPIPUL), is proposed which outperforms the state-of-the-art baselines ...
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Abstract. Fake review detection has been studied by researchers for several years. However, so far all re- ported studies are based on English reviews.
This paper reports a study of detecting fake reviews in Chinese. Our review dataset is from the Chinese review hosting site Dianping, which has built a fake ...
Although fake review detection has been studied by researchers for years using supervised learning, ground truth of large scale datasets is still unavailable ...
Concretely, we propose a novel method that with respect to its original version is much more conservative at the moment of selecting the negative examples (i.e. ...
Feb 21, 2024 · Bibliographic details on Positive Unlabeled Learning for Deceptive Reviews Detection.
Feb 28, 2015 · Deceptive Reviews Detection Based on Positive and Unlabeled Learning[J]. Journal of Computer Research and Development, 2015, 52(3): 639-648 ...