Distributed Representations
Distributed Representations for Unsupervised Semantic Role Labeling
... Our model is inspired by recent work in learning distributed representations of words (Bengio et al., 2006; Mnih and Hinton, 2008; Collobert et al., 2011; Turian et al., 2010; Mikolov et al., 2013a). In ...
10
Inducing Crosslingual Distributed Representations of Words
... Distributed representations of words have proven extremely useful in numerous natural lan- guage processing ...these representations require only unlabeled language data, which are plentiful for many ...
16
Using Distributed Representations to Disambiguate Biomedical and Clinical Concepts
... information, distributed representations encode semantic ...these representations is that they can be gen- erated from large corpora of unlabeled text, and can be trained on very large corpora in a ...
6
Distributed representations accelerate evolution of adaptive behaviours
... of distributed representations, and given the reliance of neuronal systems on distributed representa- tions, FLL-induced behaviours may constitute a significant component of apparently innate ...
28
Distributed Representations of Words and Documents for Discriminating Similar Languages
... ate distributed representations of words and sen- tences with interesting insights about the identi- fication of ...apply distributed representa- tions to other author profiling ...better ...
6
Cross lingual Dependency Parsing Based on Distributed Representations
... ing distributed representations to NLP ...of distributed representa- tions cannot be fully exploited in the generalized linear models which are adopted in most of the ex- isting NLP systems (Wang and ...
11
Distributed Representations of Geographically Situated Language
... learn representations of geographically situated ...learning representations of word meaning (Lin, 1998; Turney and Pantel, 2010; Reisinger and Mooney, 2010; Socher et ...word representations, our ...
7
Composing Distributed Representations of Relational Patterns
... We could further improve the performance of SVM + GAC by incorporating external resources in the similar manner as the previous studies did. Concretely, SVM + GAC achieved 83.7 F1 score by adding features for WordNet, ...
11
Distributed Representations of Words to Guide Bootstrapped Entity Classifiers
... The lack of labeled data to train a good entity classi- fier is one of the challenges in bootstrapped learning. We use distributed representations of words, in the form of word vectors, to guide the entity ...
6
Learning Distributed Representations of Sentences from Unlabelled Data
... of deeper language processing techniques, it is rel- atively common for models to represent phrases or sentences as continuous-valued vectors. Examples include machine translation (Sutskever et al., 2014), image ...
11
Gov2Vec: Learning Distributed Representations of Institutions and Their Legal Text
... of distributed con- tinuous vector space representations of words, we embed representations of institutions and the words from their law and policy documents into shared se- mantic ...
6
Learning Distributed Representations for Multiple-Viewpoint Melodic Prediction
... The analysis of sequences is important for extracting in- formation from music owing to its fundamentally temporal nature. In this paper, we present a distributed model based on the Restricted Boltzmann Machine ...
7
Lexical Disambiguation Based on Distributed Representations of Context Frequency
... A model for lexical disambiguation is presented that is based on combining the frequencies of past contexts of ambiguous words. The frequencies are encoded in the word representations and dene the words' ...
6
Distributed Representations of Mongolian Words and Its Efficient Estimation
... Representation of words as continuous vectors has a long history. A model architecture for estimating neural network language model (NNLM) was proposed in [1], which uses a feed forward neural network with a linear ...
7
Modeling Context sensitive Selectional Preference with Distributed Representations
... a distributed representation (Van de Cruys, 2014). The distributed framework alleviates the data sparseness problem and naturally injects the contextual information of a query argument into its word vector ...
10
Tweet2Vec: Character Based Distributed Representations for Social Media
... We propose a Bi-directional Gated Recurrent Unit (Bi-GRU) (Chung et al., 2014) neural net- work for learning tweet representations. Treat- ing white-space as a special character itself, the model does a forward ...
6
Improving Distributed Representations of Tweets Present and Future
... Twitter is a widely used microblogging platform, where users post and interact with messages, “tweets”. Understanding the semantic represen- tation of tweets can benefit a plethora of applica- tions such as sentiment ...
7
Learning Distributed Representations for Multilingual Text Sequences
... the distributed representation of word sequences in multiple ...the representations to have one vector per sentence per language, we simply force parallel sentences in the languages of consideration to ...
7
hyperdoc2vec: Distributed Representations of Hypertext Documents
... To model contents’ impact on document vectors, we simply consider an additional objective function that is identical to pv-dm, i.e., enumerate words and contexts, and use the same input [r] ...
11
Learning Hidden Markov Models with Distributed State Representations for Domain Adaptation
... perform distributed state representation learning and induce context- aware distributed word representations for domain ...a distributed representation vec- ...the distributed state ...
6