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A Simple Word Embedding Model for Lexical Substitution
... In this section we provide technical background on skip-gram embeddings, which are used in our model. As mentioned, skip-gram embeds both tar- get words and contexts in the same low-dimensional space. In this ... See full document
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Proceedings of the 1st Workshop on Vector Space Modeling for Natural Language Processing
... Poster session 1 A Simple Word Embedding Model for Lexical Substitution Oren Melamud, Omer Levy and Ido Dagan Unsupervised Text Normalization Using Distributed Representations of Words a[r] ... See full document
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Embedding Lexical Features via Tensor Decomposition for Small Sample Humor Recognition
... of word embeddings as inputs to neural models (Bertero and Fung, 2016; Donahue et ...include word frequency (Mihalcea and Strapparava, 2005), n-gram proba- bility (Yan and Pedersen, 2017), and ... See full document
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Supervised All Words Lexical Substitution using Delexicalized Features
... accurate lexical substitution systems use supervised machine learning to train (and test) a separate classifier per target word, using lexical and shallow syntactic ...each word. Bie- ... See full document
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Turk Bootstrap Word Sense Inventory 2.0: A Large-Scale Resource for Lexical Substitution
... between model size and classification ...supervised word sense disambiguation system for any sense-labelled ...(SemEval lexical sample task 2007; see Pradhan, 2007) showed that the system compares ... See full document
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Exploration of register dependent lexical semantics using word embeddings
... analysing word co-occurrences. The trained model can represent semantics of a given word as a sequence of its ‘nearest associates’: words closest to the key word by the cosine similarity of ... See full document
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Tempo Lexical Context Driven Word Embedding for Cross Session Search Task Extraction
... which simple approaches of grouping queries by their timestamps, ...ing lexical similarity for clustering cross-session queries into a single group, ... See full document
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Joint Embedding of Query and Ad by Leveraging Implicit Feedback
... including simple lexical similarity scores between the query and ads, word or phrase over- laps and the number of overlapping words and charac- ...of simple lexical similarity cannot ... See full document
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Pre Computable Multi Layer Neural Network Language Models
... a simple technique for speeding up feed-forward embedding-based neural network models, where the dot product be- tween each word embedding and part of the first hidden layer are pre-computed ... See full document
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Supervising Unsupervised Open Information Extraction Models
... of lexical and syntactic information such as word embedding, part-of- speech embedding, syntactic role embedding and dependency structure as its input features and produces a sequence ... See full document
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BERT based Lexical Substitution
... BERT-based lexical substitution approach, moti- vated by that BERT (Devlin et ...target word conditioned on its bi-directional contexts but also can measure two sentences’ contextualized ... See full document
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Personalized Substitution Ranking for Lexical Simplification
... A lexical simplification (LS) system substi- tutes difficult words in a text with simpler ones to make it easier for the user to under- ...original word. We propose a personalized ap- proach for ... See full document
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Learning Phrase Embeddings from Paraphrases with GRUs
... the word embed- ding space (Socher et ...the model on para- ...the embedding of “Amer- ica”. However, since the embedding of “America” is kept constant, transformations on “the United States” ... See full document
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Baseline Needs More Love: On Simple Word Embedding Based Models and Associated Pooling Mechanisms
... simpler word-embedding-based architectures exhibit comparable or even superior performance, compared with more-sophisticated models using recurrence or convolutions (Parikh et ...the word em- bedding ... See full document
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“Let Everything Turn Well in Your Wife”: Generation of Adult Humor Using Lexical Constraints
... We proved empirically that, in this setting, hu- mor generation is more effective when using a list of taboo words. The other strong empirical re- sult regards the context of substitutions: using bi- grams to ... See full document
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Probabilistic models of similarity in syntactic context
... English Lexical Substitution task, run as part of the SemEval-1 competition, required participants to propose good substitutes for a set of target words in various sentential contexts (McCarthy and Nav- ... See full document
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Word Sense Filtering Improves Embedding Based Lexical Substitution
... Lexical substitution experiments are usually eval- uated using generalized average precision (GAP) (Kishida, ...target word to be the candidates, and we set the test set annotator fre- quency to be ... See full document
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Automatically Linking Lexical Resources with Word Sense Embedding Models
... lexicographic word senses with word sense em- beddings by retrieving sets of senses related to the different meanings of a lemma and measuring the similarity between their vector ...and embedding ... See full document
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PIC a Different Word: A Simple Model for Lexical Substitution in Context
... In this work, we limit our comparisons to the model of Melamud et al. (2015b), a method which performs nearly state-of-art, is extremely easy to implement, and is a good testbed for focused hy- potheses. They ... See full document
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Lexical Substitution Dataset for German
... good substitution, at least 2 other subjects were able to do ...target word and they tended to mark those sentences with a higher degree of ...this word (despite those not being presented sequen- ... See full document
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