[PDF] Top 20 Semantic Information Extraction for Improved Word Embeddings
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Semantic Information Extraction for Improved Word Embeddings
... create word embed- ...target word. Fur- ther analysis revealed that their word embeddings capture more functional but less topical ...existing word embeddings in order to bring ... See full document
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Combining Word Embeddings and Feature Embeddings for Fine grained Relation Extraction
... While compositional models aim to learn higher- level structure representations, composition of em- beddings alone may not capture important syntac- tic or semantic patterns. Consider the task of re- lation ... See full document
6
Symmetric Pattern Based Word Embeddings for Improved Word Similarity Prediction
... the extraction of ...using word co-occurrence statistics, manually and automatically induced pat- terns, the WordNet lexicon and thesauri (Lin et ...proposed word represen- tation methods that assign ... See full document
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A study of semantic augmentation of word embeddings for extractive summarization
... utilize semantic infor- mation in the text, we use the WordNet seman- tic graph (Miller, 1995), a lexical database for English, often used as an external information source for machine learning research in ... See full document
10
Deep Multilingual Correlation for Improved Word Embeddings
... related information to lie in nonlinear subspaces of the original ...DCCA-transformed embeddings on word similarity tasks like WordSim-353 (Finkelstein et ...original embeddings and over ... See full document
7
Proceedings of the BioNLP 2018 workshop
... Manirupa Das, Eric Fosler-Lussier, Simon Lin, Soheil Moosavinasab, David Chen, Steve Rust, Yungui Huang and Rajiv Ramnath . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . ... See full document
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Semantic Similarity of Arabic Sentences with Word Embeddings
... each word in each ...in information retrieval (Tur- ney and Pantel, 2010) and can be employed in our ...much information the word provides, that is, whether the term that occurs infrequently ... See full document
7
AutoExtend: Combining Word Embeddings with Semantic Resources
... distributed word representations and semantic resources to create better or specialized ...a Semantic Word Embedding ...learn embeddings that are optimized to predict a related ... See full document
25
Learning Semantic Hierarchies via Word Embeddings
... pernym extraction of entity names, but it is unsuit- able for semantic hierarchy construction which in- volves many words with broad ...the word semantics ... See full document
11
Using bilingual word embeddings for multilingual collocation extraction
... the extraction with confidence values higher than 90% does not increase the precision of the system, so we can infer that the errors pro- duced in the most confident pairs arise due fac- tors other than the ... See full document
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A supervised approach to taxonomy extraction using word embeddings
... the information that is behind these ...onomy extraction and consists of two key steps. Firstly, in the term extraction step the set of terms that are relevant can be extracted from a collection of ... See full document
6
Adjusting Word Embeddings with Semantic Intensity Orders
... such semantic inten- sity scales can help correct processing in down- stream tasks that require robust textual under- ...correct information about se- mantic scales can also provide accurate inferences: ... See full document
8
Domain Adapted Word Embeddings for Improved Sentiment Classification
... quality word embeddings that capture domain specific semantics and are suitable for tasks on the specific ...(DA) embeddings are obtained by com- bining generic embeddings and Domain Specific ... See full document
6
Domain Adapted Word Embeddings for Improved Sentiment Classification
... monolingual word embed- dings across data sets in different application do- mains/contexts for the purpose of a given down- stream task such as sentiment ...ing word embeddings across different ... See full document
9
Aggregating Continuous Word Embeddings for Information Retrieval
... descriptor-level information and therefore incur a lower loss of ...a semantic standpoint and words can be embedded in a continuous space as is done for instance in ... See full document
10
Specializing Word Embeddings (for Parsing) by Information Bottleneck
... Pre-trained word embeddings like ELMo and BERT contain rich syntactic and semantic in- formation, resulting in state-of-the-art perfor- mance on various ...variational information bottleneck ... See full document
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Probing for Semantic Classes: Diagnosing the Meaning Content of Word Embeddings
... the word embedding space. Word sense disambiguation (WSD) (Agirre and Edmonds, 2007; Navigli, 2009) and entity link- ing (EL) (Bagga and Baldwin, 1998; Mihalcea and Csomai, 2007) are related to ambiguity in ... See full document
14
Learning Semantic Word Embeddings based on Ordinal Knowledge Constraints
... incorporate semantic knowledge into the popular data-driven learning pro- cess of word embeddings to improve the quality of ...represent semantic knowledge as many ordinal ranking inequalities ... See full document
11
Semantic Annotation Aggregation with Conditional Crowdsourcing Models and Word Embeddings
... encode semantic and syntactic meaning (Mikolov et ...relation extraction (Nguyen and Grishman, 2014), and part of speech induction (Lin et ...that semantic, vector-based text representations can help ... See full document
10
Incorporating Syntactic and Semantic Information in Word Embeddings using Graph Convolutional Networks
... Word embeddings have been widely adopted across several NLP ...ing word embedding methods utilize sequen- tial context of a word to learn its ...a word, such meth- ods result in an ... See full document
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