[PDF] Top 20 Learning Semantic Textual Similarity from Conversations
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Learning Semantic Textual Similarity from Conversations
... cosine similarity between the encoded rep- resentations of the sentence ...learned from conversations in capturing general- purpose semantic ...pulled from turns in a ... See full document
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Semantic Textual Similarity with Siamese Neural Networks
... Given that a good STS metric is required for a variety of NLP fields, researchers have pro- posed a large number of such metrics. Before the shift of interest in neural networks, most of the proposed methods relied ... See full document
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Correlation Coefficients and Semantic Textual Similarity
... into semantic tex- tual similarity has focused on constructing state-of-the-art embeddings using sophisti- cated modelling, careful choice of learning signals and many clever ...cosine ... See full document
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Learning the Impact and Behavior of Syntactic Structure: A Case Study in Semantic Textual Similarity
... ture from syntactic parsing information, particu- larly, the Partial Tree (PT) kernel is proposed as a new convolution kernel to fully exploit depen- dency ... See full document
9
Determining Semantic Textual Similarity using Natural Deduction Proofs
... for learning textual ...for learning textual ...calculated from the probabilities of their ground atoms and are extracted as ...derived from the entailment results of first-order ... See full document
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Using Semantic Similarity as Reward for Reinforcement Learning in Sentence Generation
... corpora from multi30k-dataset (Elliott et ...of textual descrip- tions of images while the WIT3 consists of tran- scribed TED ...sets from each corpus for ... 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 ...scale from ... See full document
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Neural Models for Detecting Binary Semantic Textual Similarity for Algerian and MSA
... Detecting Semantic Textual Similarity (STS) aims to predict a relationship between a pair of sen- tences based on a semantic similarity ...detecting semantic similarity ... See full document
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A Semantically Enhanced Approach to Determine Textual Similarity
... derived from dependency parses and named ...logic from transformations, use a modified resolution step and extract hundreds of features from the ...chine learning to determine ... See full document
11
Multi Task Learning for Semantic Relatedness and Textual Entailment
... The semantic relatedness (a.k.a. semantic textual similarity) and textual en- tailment are two related semantic level NLP ...the semantic equivalence between two ... See full document
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Learning the Impact of Machine Translation Evaluation Metrics for Semantic Textual Similarity
... Next, we combine the outputs of these four met- rics to build eight different regression models us- ing different classification algorithms in WEKA (e.g. IsotonicRegression, LeastMedSq, Mul- tilayerPerceptron, ... See full document
6
Learning Semantic Textual Similarity with Structural Representations
... the learning algorithm to extract useful syntactic and shallow semantic ...structural learning approach to STS is conceptually simple and does not re- quire additional linguistic sources other than ... See full document
5
Cross lingual Learning of Semantic Textual Similarity with Multilingual Word Representations
... assessing semantic content of two sentences notably does not take important se- mantic features such as negation into account, and can therefore be seen as complimentary to textual ...the semantic ... See full document
5
If Sentences Could See: Investigating Visual Information for Semantic Textual Similarity
... signals from visual and linguistic input tend to outperform uni-modal models exploiting only linguistic information across a variety of semantic ...measuring semantic textual similarity ... See full document
15
Rule based vs Neural Net Approaches to Semantic Textual Similarity
... sentences. From the results we observe that our system beats the third-ranked performer on the MSRpar corpus, and the second- and third-ranked performers on the SMTeuroparl corpus, which contains mainly long ... See full document
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Frequently Asked Questions Retrieval for Croatian Based on Semantic Textual Similarity
... Semantic gap. Taken to the extreme, a para- phrase can change a query to the extent that it not only introduces a lexical gap, but also a se- mantic gap, whose bridging would require logi- cal inference and world ... See full document
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Identifying Prominent Arguments in Online Debates Using Semantic Textual Similarity
... Another observation concerns the level of argu- ment granularity. In the previous analysis, we used the gold number of clusters. We note, however, that the level of granularity is to a certain extent arbitrary. To ... See full document
6
Extending Monolingual Semantic Textual Similarity Task to Multiple Cross lingual Settings
... We extended these datasets for cross-lingual settings by assuming that the gold similarity scores (ranged in [0,5]) are preserved even for the translated sentence pairs. More specifically, we translated one-half ... See full document
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What Do We Learn from Word Associations? Evaluating Machine Learning Algorithms for the Extraction of Contextual Word Meaning in Natural Language Processing
... Keywords: Machine Learning; Algorithms; Natural Language Processing, Deep Learning, Vector 29.. Space Models, Semantic Similarity, Distributional Semantics, Latent Semantic Analys[r] ... See full document
21
A Survey of Text Similarity Approaches
... Machine Learning, in the department of Computer Science. He graduated from the Department of Computer Engineering, Technical College with honor ...degree from the National School of Space and ... See full document
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