[PDF] Top 20 Learning Semantic Textual Similarity with Structural Representations
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Learning Semantic Textual Similarity with Structural Representations
... the learning algorithm to extract useful syntactic and shallow semantic ...different structural representations, ...learned structural models are used to obtain pre- diction scores thus ... See full document
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Using Semantic Similarity as Reward for Reinforcement Learning in Sentence Generation
... For machine translation, we used De-En par- allel corpora from multi30k-dataset (Elliott et al., 2016) and WIT3 (Cettolo et al., 2012). The multi30k-dataset is comprised of textual descrip- tions of images while ... See full document
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Learning Contextual Embeddings for Structural Semantic Similarity using Categorical Information
... Word Similarity Network The methods to model the context described in ...a similarity between two words dependent on the sentences which they belong ... See full document
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Semantic Textual Similarity with Siamese Neural Networks
... Given the growing importance of having a good STS metric and as a result of the Se- mEval workshops, researchers have proposed numerous STS methods. Most of the early approaches were based on traditional machine ... See full document
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Determining Semantic Textual Similarity using Natural Deduction Proofs
... Determining semantic textual similarity is a core research subject in natural language ...tic representations capture deeper levels of sentence semantics, but their symbolic na- ture does not ... See full document
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Probabilistic Soft Logic for Semantic Textual Similarity
... mantic Textual Similarity ...tic representations of sentences with soft infer- ence rules for lexical and phrasal similarities com- puted from distributional ... See full document
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Learning the Impact and Behavior of Syntactic Structure: A Case Study in Semantic Textual Similarity
... the structural relationships between two ...alternative structural repre- sentation in which words are linked in a way that words are always at the leaf ... See full document
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If Sentences Could See: Investigating Visual Information for Semantic Textual Similarity
... compute similarity scores for given pairs of ...word similarity measures as the sole information source guiding the alignment ...the similarity scores for all pairs of words between the sentences S 1 ... See full document
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Extending Monolingual Semantic Textual Similarity Task to Multiple Cross lingual Settings
... • Additionally, we assess a combined approach (ML+), which incorporates the alignment score as an addi- tional feature in the machine learning process. As in the conventional STS tasks, the end-to-end predic- tion ... See full document
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Neural Models for Detecting Binary Semantic Textual Similarity for Algerian and MSA
... various semantic-related tasks. Among others, machine learning has been applied to detect semantic textual relatedness such as Tex- tual Entailment (TE) (Nielsen et ...syntactic, ... See full document
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Learning Monolingual Compositional Representations via Bilingual Supervision
... Sentence Representations Following Wieting et ...four Semantic Textual Simi- larity (STS) datasets (Agirre et ...of similarity on a 1 to 5 scale. Systems have to out- put a similarity ... See full document
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Textual and structural approaches to detecting figure plagiarism in scientific publications
... for similarity detection were mostly based on the character-based, word-based, or ...two representations based on longest characters substring (LCS) and a 2 word N-gram representation for measuring the ... See full document
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AN EFFECTIVE TECHNIQUE FOR BRAIN TUMOUR SEGMENTATION AND DETECTION USING CUCKOO BASED NEURO FUZZY CLASSIFIER
... figure similarity, there are little attentions found in the research community to detect any of the instances of figure plagiarism such as manipulating figures by changing the structure of the figure, inserting, ... See full document
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A Preliminary Evaluation of the Impact of Syntactic Structure in Semantic Textual Similarity and Semantic Relatedness Tasks
... Individual approach evaluation. Each syntactic approach is weaker than both baselines. Though the STK and DTK both use the tree kernel approach, just different representations, the performance is similar only on ... See full document
7
Correlation Coefficients and Semantic Textual Similarity
... from learning word embeddings as point estimates and instead model words as parametric densities (Vilnis and McCallum, 2014; Barkan, 2017; Athi- waratkun and Wilson, ...such representations need to be ... See full document
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Learning the Impact of Machine Translation Evaluation Metrics for Semantic Textual Similarity
... dicting semantic similarity scores in Se- mantic Textual Similarity (STS) task for English, in light of their usage for para- phrase ...the semantic scale [0-5] of the STS ... See full document
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Neural Networks for Semantic Textual Similarity
... Semantic textual similarity matching is the task of determining the resemblance of the meanings between two ...2017 Semantic Textual Similarity corpus 1 2 ...of semantic ... See full document
10
Learning Semantic Textual Similarity from Conversations
... internal representations of such models resolve the semantics necessary to pre- dict the correct response across a broad selec- tion of input ...Meaning similarity be- tween sentences then can be obtained ... See full document
11
Cross lingual Learning of Semantic Textual Similarity with Multilingual Word Representations
... In all cases, training on the target language pair is beneficial. We also observe that using multilingual embeddings is crucial for multilingual approaches, as monolingual embeddings naturally only yield on-par results ... See full document
5
Identifying Prominent Arguments in Online Debates Using Semantic Textual Similarity
... for each topic. Results are shown in Table 1. Overall, the best model is skip-gram with Ward’s linkage, generally outperforming the other models considered in terms of both ARI and V-measure. This model also results in ... See full document
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