In this paper, we contribute to this situation by comparing several models on six different benchmarks, which belong to different domains and additionally have ...

Sep 13, 2017 · In this paper, we contribute to this situation by comparing several models on six different benchmarks, which belong to different domains and additionally have ...

Dec 14, 2024 · With our experiments, we contribute to a better understanding of the performance of different model architectures on different data sets.

Barnes, Jeremy; Klinger, Roman; Schulte im Walde, Sabine (2017): Assessing State-of-the-Art Sentiment Models on State-of-the-Art Sentiment Datasets, ...

Assessing State-of-the-art Sentiment Models on State-of-the-art Sentiment Datasets ... This experiment runs the best models with the best embeddings as described ...

Assessing State-of-the-art Sentiment Models on State-of-the-art Sentiment Datasets. Barnes, Jeremy, Roman Klinger, and Sabine Schulte im Walde. WASSA 2017. [ ...

Incorporating sentiment information into word embeddings during training gives good results for datasets that are lexically similar to the training data.

Dec 19, 2024 · The study's objective was to use a Deep Learning methodology to analyze movie reviews and compare the results with other Deep Learning ...

In this paper, we aim to deploy and evaluate the performances of the State-of-the-Art machine learning sentiment analysis techniques on a public IMDB dataset.

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