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Found 14 papers, 2 papers with code
The FairyNet Corpus - Character Networks for German Fairy Tales
The release of this corpus provides an opportunity of training and comparing different algorithms for the extraction of character networks, which so far was barely possible due to heterogeneous interests of previous researchers.
LSX_team5 at SemEval-2022 Task 8: Multilingual News Article Similarity Assessment based on Word- and Sentence Mover’s Distance
This paper introduces our submission for the SemEval 2022 Task 8: Multilingual News Article Similarity.
WueDevils at SemEval-2022 Task 8: Multilingual News Article Similarity via Pair-Wise Sentence Similarity Matrices
We present a system that creates pair-wise cosine and arccosine sentence similarity matrices using multilingual sentence embeddings obtained from pre-trained SBERT and Universal Sentence Encoder (USE) models respectively.
Towards a Computational Analysis of Suspense: Detecting Dangerous Situations
Suspense is an important tool in storytelling to keep readers engaged and wanting to read more.
One Graph to Rule them All: Using NLP and Graph Neural Networks to analyse Tolkien's Legendarium
Natural Language Processing and Machine Learning have considerably advanced Computational Literary Studies.
Detecting Scenes in Fiction: A new Segmentation Task
This paper introduces the novel task of scene segmentation on narrative texts and provides an annotated corpus, a discussion of the linguistic and narrative properties of the task and baseline experiments towards automatic solutions.
Where to Submit? Helping Researchers to Choose the Right Venue
Whenever researchers write a paper, the same question occurs: {``}Where to submit?
Improving Sentiment Analysis with Biofeedback Data
Humans frequently are able to read and interpret emotions of others by directly taking verbal and non-verbal signals in human-to-human communication into account or to infer or even experience emotions from mediated stories.
SimLoss: Class Similarities in Cross Entropy
One common loss function in neural network classification tasks is Categorical Cross Entropy (CCE), which punishes all misclassifications equally.
MapLUR: Exploring a new Paradigm for Estimating Air Pollution using Deep Learning on Map Images
In this paper, we advocate a paradigm shift for LUR models: We propose the Data-driven, Open, Global (DOG) paradigm that entails models based on purely data-driven approaches using only openly and globally available data.
Team Xenophilius Lovegood at SemEval-2019 Task 4: Hyperpartisanship Classification using Convolutional Neural Networks
This paper describes our system for the SemEval 2019 Task 4 on hyperpartisan news detection.
ClaiRE at SemEval-2018 Task 7: Classification of Relations using Embeddings
In this paper we describe our system for SemEval-2018 Task 7 on classification of semantic relations in scientific literature for clean (subtask 1. 1) and noisy data (subtask 1. 2).
ClaiRE at SemEval-2018 Task 7 - Extended Version
Due to these changes Classification of Relations using Embeddings (ClaiRE) achieved an improved F1 score of 75. 11% for the first subtask and 81. 44% for the second.
Analyzing Features for the Detection of Happy Endings in German Novels
With regard to a computational representation of literary plot, this paper looks at the use of sentiment analysis for happy ending detection in German novels.
