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Found 23 papers, 2 papers with code
SEQ\^3: Differentiable Sequence-to-Sequence-to-Sequence Autoencoder for Unsupervised Abstractive Sentence Compression
The proposed model does not require parallel text-summary pairs, achieving promising results in unsupervised sentence compression on benchmark datasets.
Neural Activation Semantic Models: Computational lexical semantic models of localized neural activations
Neural activation models have been proposed in the literature that use a set of example words for which fMRI measurements are available in order to find a mapping between word semantics and localized neural activations.
Tweester at SemEval-2017 Task 4: Fusion of Semantic-Affective and pairwise classification models for sentiment analysis in Twitter
In this paper, we describe our submission to SemEval2017 Task 4: Sentiment Analysis in Twitter.
Crossmodal Network-Based Distributional Semantic Models
Despite the recent success of distributional semantic models (DSMs) in various semantic tasks they remain disconnected with real-world perceptual cues since they typically rely on linguistic features.
The SpeDial datasets: datasets for Spoken Dialogue Systems analytics
The SpeDial consortium is sharing two datasets that were used during the SpeDial project.
Cognitively Motivated Distributional Representations of Meaning
Although meaning is at the core of human cognition, state-of-the-art distributional semantic models (DSMs) are often agnostic to the findings in the area of semantic cognition.
Affective Lexicon Creation for the Greek Language
Starting from the English affective lexicon ANEW (Bradley and Lang, 1999a) we have created the first Greek affective lexicon.
Word Semantic Similarity for Morphologically Rich Languages
In this work, we investigate the role of morphology on the performance of semantic similarity for morphologically rich languages, such as German and Greek.
SemSim: Resources for Normalized Semantic Similarity Computation Using Lexical Networks
We investigate the creation of corpora from web-harvested data following a scalable approach that has linear query complexity.
Associative and Semantic Features Extracted From Web-Harvested Corpora
We address the problem of automatic classification of associative and semantic relations between words, and particularly those that hold between nouns.
