Titlebook: Computational Linguistics and IntelligentText Processing; 20th International C Alexander Gelbukh Conference proceedings 2023 Springer Natur

Grating

Gossamer

Opinion Spam Detection with Attention-Based LSTM Networkse important features. This paper describes our approach to apply LSTM and attention-based mechanisms for detecting deceptive reviews. Experiments with the Three-domain data set [.] show that a BiLSTM model coupled with Multi-Headed Self Attention improves the F-measure from 81.49% to 87.59% in detecting fake reviews.

窒息

变白

Kontinuumsbegriff und Kinematik,words effectively, we introduce root and entity tag embedding plus tensor layer to the neural networks. The effects of those are significant for improving NER model performance of MCLs. The proposed models outperform state-of-the-art including character-based approaches, and can be potentially applied to other morphologically complex languages.

Optic-Disk

https://doi.org/10.1007/978-3-540-38441-0t uses character-based distributed representations to classify words into categories in the dictionary. The recognizer then uses the output of the classification as an additional feature. We conducted experiments to recognize named entities in recipe text and report the results to demonstrate the performance of our method.

不能逃避

Acetabulum

,Grundzüge turbulenter Strömungen,rimental results on five different Chinese sentiment analysis datasets show that the inclusion of phonetic features significantly and consistently improves the performance of textual and visual representations.

灌输

MAIZE

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