[PDF] Top 20 Learning Text Similarity with Siamese Recurrent Networks
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Learning Text Similarity with Siamese Recurrent Networks
... Measuring the semantic similarity between texts is also fundamental problem in Information Extraction (IE) (Martin and Jurafsky, 2000). An important step in many applications is normaliza- tion, which puts pieces ... See full document
10
Learning Relational Representations by Analogy using Hierarchical Siamese Networks
... relational similarity score is ...mentions) similarity with the aim to prove that our pre-trained siamese model is able to grasp the semantics of relations better than the other pre-trained ... See full document
11
De Mixing Sentiment from Code Mixed Text
... for text normalization and senti- ment analysis of code-mixed ...trastive learning with Siamese networks to map code-mixed and standard language text to a com- mon sentiment space ... See full document
7
Learning Discriminative Projections for Text Similarity Measures
... framework, Similarity Learning via Siamese Neural Network (S2Net), to discriminatively learn the concept vector representations of input text ob- ...general Siamese neural network ... See full document
10
Siamese Convolutional Networks for Cognate Identification
... the similarity between word ...machine learning algorithms to determine if a pair of words are cognates or ...orthographic similarity measures as features for the machine learning ...machine ... See full document
10
A Sentence Similarity Estimation Method Based on Improved Siamese Network
... generated Siamese neural net- work, a special recurrent neural network using the LSTM, which generates a dense vector that represents the idea of each ...of recurrent neural net- works, especially ... See full document
14
Statistical Script Learning with Recurrent Neural Networks
... from text, by modeling and inferring events comprising a subset of the document’s syn- tactic dependency ...raw text level. In particular, we inves- tigate the performance of a text-level sentence ... See full document
6
Learning Text Pair Similarity with Context sensitive Autoencoders
... neural networks because these models are often trained with only local informa- tion about their individual ...example, recurrent and recursive neural networks only use local information about ... See full document
11
Deep Neural Models for Medical Concept Normalization in User Generated Texts
... free-form text to a concept in a con- trolled vocabulary, usually to the standard the- saurus in the Unified Medical Language Sys- tem ...sequence learning problem with powerful neural networks such ... See full document
7
Data driven Approaches to Author’s Profiling Identification for Russian Texts on Base of Complex Machine Learning Models in Combinations with Siamese Networks
... There are different formulations of the task of author profiling, in particular for age and gender identification. In particular, in [4] binary age prediction was used: whether the age of a text author is under or ... See full document
6
Multi Module Recurrent Neural Networks with Transfer Learning
... in some vector space, but also to training full mod- els that solve some non-trivial sequential problem, in order to apply them later to another one. Our approach is similar to Conneau et al. (2017) where authors ... See full document
5
Inducing Multilingual Text Analysis Tools Using Bidirectional Recurrent Neural Networks
... on recurrent neural networks (RNN) to induce multi- lingual text analysis ...multi-task learning to build systems that simultaneously perform syntactic and semantic ... See full document
11
The Rise of Deep Learning in Radiology: An Overview of Recent Research
... deep learning techniques in the field of ...deep learning has pervaded every field and the deep learning revolution has opened up new frontiers in artificial ...deep learning techniques are ... See full document
9
Semantic Textual Similarity with Siamese Neural Networks
... the Siamese neural net- work architecture used in our experiments is shown in Figure ...a Recurrent Neural Network (RNN) cell which learns a mapping from the space of variable length sequences of ... See full document
8
Unified Framework For Deep Learning Based Text Classification
... Deep learning has emerged as a very popular approach for solving large scale pattern recognition ...various text mining problems with improved accuracy as compared to pre-existing ...deep learning ... See full document
5
Supervised Rhyme Detection with Siamese Recurrent Networks
... A SRN consists of two identical recurrent sub-networks that learn a vector representation from input pairs. The sub-networks each receive a rhyme word as character embedding vector and encode it ... See full document
6
Replicated Siamese LSTM in Ticketing System for Similarity Learning and Retrieval in Asymmetric Texts
... deep learning, the STS task has gained success using LSTM (Mueller and Thyagarajan, 2016) and CNN (Yin et ...semantic similarity between example pairs, each with a single sentence or phrase with term ... See full document
11
Learning to Disentangle Interleaved Conversational Threads with a Siamese Hierarchical Network and Similarity Ranking
... deep learning methods in represen- tation learning (Bengio et ...as text (Hinton and Salakhut- dinov, ...embedded text sequences (Blunsom et ...as text classification (Kim, 2014; Lai et ... See full document
11
Cascade recurring deep networks for audible range prediction
... neural networks with many output variables, learning of weight w is difficult because there are many connections to hidden ...neural networks are independently configured for each output variable, it ... See full document
10
Proceedings of the 2016 Conference on Empirical Methods in Natural Language Processing
... by learning decision- theoretic models for communication, action, and ...for learning how to plan in very large, uncer- tain state-action spaces by using hierarchical ... See full document
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