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TextRank: Bringing Order into Text
TLDR
In this paper, the authors introduce TextRank, a graph-based ranking model for text processing, and show how this model can be successfully used in natural language applications. Expand
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Corpus-based and Knowledge-based Measures of Text Semantic Similarity
TLDR
This paper presents a method for measuring the semantic similarity of texts, using corpus-based and knowledge-based measures of similarity. Expand
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Wikify!: linking documents to encyclopedic knowledge
TLDR
This paper introduces the use of Wikipedia as a resource for automatic keyword extraction and word sense disambiguation, and shows how this online encyclopedia can be used to achieve state-of-the-art results on both these tasks. Expand
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SemEval-2007 Task 14: Affective Text
TLDR
The "Affective Text" task focuses on the classification of emotions and valence (positive/negative polarity) in news headlines, and is meant as an exploration of the connection between emotions and lexical semantics. Expand
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Learning to identify emotions in text
TLDR
We propose and evaluate several knowledge-based and corpusbased methods for the automatic identification of these emotions in text. Expand
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The Senseval-3 English lexical sample task
TLDR
This paper presents the task definition, resources, participating systems, and comparative results for the English lexical sample task, which was organized as part of the SENSEVAL-3 evaluation exercise. Expand
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Measuring the Semantic Similarity of Texts
TLDR
We introduce a knowledge-based method that combines word-to-word similarity metrics into a text similarity metric, and we show that this method outperforms the traditional text similarity metrics based on lexical matching. Expand
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MELD: A Multimodal Multi-Party Dataset for Emotion Recognition in Conversations
TLDR
We propose the Multimodal EmotionLines Dataset (MELD), a large-scale multimodal multi-party emotional conversational database containing more than two speakers per dialogue. Expand
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Automatic Detection of Fake News
TLDR
The proliferation of misleading information in everyday media outlets such as social media feeds, news blogs, and online newspapers have made it challenging to identify trustworthy news sources, thus increasing the need for computational tools able to provide insights into the reliability of online content. Expand
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Text-to-Text Semantic Similarity for Automatic Short Answer Grading
TLDR
In this paper, we explore unsupervised techniques for the task of automatic short answer grading. Expand
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