[PDF] Top 20 On the contribution of word embeddings to temporal relation classification
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On the contribution of word embeddings to temporal relation classification
... This temporal information is often modelled as a graph, with times and events/states as the nodes and temporal relations holding between them as the ...ordering temporal entities, i.e., the ... See full document
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Temporal Word Analogies: Identifying Lexical Replacement with Diachronic Word Embeddings
... A thorough investigation into the relative ben- efits of the different methods listed above would be a valuable contribution to future work in this area. In the present work, I take a global linear regression ... See full document
6
Urdu Word Embeddings
... on word similarity tasks like WordSim-353 and SimLex-999 that test vector space models’ ability to learn semantic relations between word ...The embeddings are made publicly available online 2 for ... See full document
5
Classification and Clustering of Arguments with Contextualized Word Embeddings
... argument classification and clustering and dis- cuss how contextualized word embeddings can help to improve these tasks across four different ...tualized word embeddings help to improve ... See full document
12
Searching for the X Factor: Exploring Corpus Subjectivity for Word Embeddings
... the word embeddings, and input corpora may be dif- ferentially informative towards various NLP ...ment classification, revolve around subjective ex- pressions of likes or ...topic ... See full document
10
Word Relation Autoencoder for Unseen Hypernym Extraction Using Word Embeddings
... for relation extraction to handle unseen ...a relation pair or not. (3) We propose a novel Word Relation Autoencoder (WRAE) which can effectively reduce ... See full document
6
Aspectual Type and Temporal Relation Classification
... matic temporal relation classification have not in- corporated this sort of semantic ...Our contribution with this paper is to incor- porate this sort of information in existing ma- chine ... See full document
10
An LSTM Approach to Short Text Sentiment Classification with Word Embeddings
... For more complex relations, deep learning methods are adopted, which utilize multiple hidden layers. With deeper network structures, it usually takes more computing time. These methods were made feasible thanks to the ... See full document
10
Improving Implicit Discourse Relation Recognition with Discourse specific Word Embeddings
... connective classification. The connective classification task predicts which discourse con- nective is suitable for combining two given argu- ...implicit relation recognition can be easily used for ... See full document
6
Temporal Relation Classification in Persian and English contexts
... Persian Temporal Relation Classifier (PTRC) that finds the type of temporal relations between pairs of events in the Persian ...the classification by applying new features and SSK, but also ... See full document
9
Discourse Relation Sense Classification Using Cross argument Semantic Similarity Based on Word Embeddings
... each word in Arg1, we choose the most similar word from the yield of Arg2 and we take the average of all best word pair similarities, as suggested in Tran et ...based word vector sim- ... See full document
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Vector space semantics with frequency driven motifs
... While word embeddings and lan- guage models from such methods have been use- ful for tasks such as relation classification, polarity detection, event coreference and parsing; much of existing ... See full document
10
Task Oriented Learning of Word Embeddings for Semantic Relation Classification
... each relation class after the supervised learning step of ...n-gram embeddings capture salient syntactic patterns which are useful for the relation classification ... See full document
11
Relational Word Embeddings
... Standard word embedding models tend to cap- ture semantic similarity rather well (Baroni et ...tional word embeddings should allow us to model such properties in a more consistent and transpar- ent ... See full document
11
Morphological Word Embeddings
... Continuous word-embeddings have been shown to capture most of these shades of similarity to some ...guiding word-embeddings with mor- phologically annotated data, a form of semi- supervised ... See full document
6
Word Embeddings and Convolutional Neural Network for Arabic Sentiment Classification
... sentiment classification, which evaluates and detects the sentiment polarity from Arabic reviews and Arabic social media, is ...neural word embeddings using a ...Arabic word embeddings ... See full document
10
Towards Unsupervised Text Classification Leveraging Experts and Word Embeddings
... Those include semi-supervised techniques that seek to leverage a small set of labeled documents to derive labels for the remainder of the cor- pus. For instance, Nigam et al. (2000) propose to follow the ... See full document
9
Exploiting Timegraphs in Temporal Relation Classification
... real-world temporal relation classification ...the temporal relation classification task, the system with only baseline features is able to achieve good classification re- ... See full document
9
UDPipe at SIGMORPHON 2019: Contextualized Embeddings, Regularization with Morphological Categories, Corpora Merging
... Tables 5 and 6 present detailed results of our best system from Table 4. Note that while this sys- tem is not our competition entry, it utilizes the same models as the competition entry, only com- bined in a different ... See full document
9
Word Embeddings vs Word Types for Sequence Labeling: the Curious Case of CV Parsing
... of word types incorporating all tokens that occur at least twice in the training ...implement word embeddings of any given word type as one feature per ... See full document
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