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Found 11 papers, 0 papers with code
An Iterative Approach for Unsupervised Most Frequent Sense Detection using WordNet and Word Embeddings
Given a word, what is the most frequent sense in which it occurs in a given corpus?
Indian Language Wordnets and their Linkages with Princeton WordNet
Linked wordnets are extensions of wordnets, which link similar concepts in wordnets of different languages.
Semi-automatic WordNet Linking using Word Embeddings
Thus techniques that can aid the experts are desirable.
Utilizing Wordnets for Cognate Detection among Indian Languages
Automatic Cognate Detection (ACD) is a challenging task which has been utilized to help NLP applications like Machine Translation, Information Retrieval and Computational Phylogenetics.
Eyes are the Windows to the Soul: Predicting the Rating of Text Quality Using Gaze Behaviour
Such subjective aspects are better handled using cognitive information.
Treat us like the sequences we are: Prepositional Paraphrasing of Noun Compounds using LSTM
It has been observed that uncovering the preposition is a significant step towards uncovering the predicate.
Towards Lower Bounds on Number of Dimensions for Word Embeddings
More specifically, we show that the number of pairwise equidistant words of the corpus vocabulary (as defined by some distance/similarity metric) gives a lower bound on the the number of dimensions , and going below this bound results in degradation of quality of learned word embeddings.
Adapting Pre-trained Word Embeddings For Use In Medical Coding
We add information from medical coding data, as well as the first level from the hierarchy of ICD-10 medical code set to different pre-trained word embeddings.
Are Word Embedding-based Features Useful for Sarcasm Detection?
For example, this augmentation results in an improvement in F-score of around 4\% for three out of these four feature sets, and a minor degradation in case of the fourth, when Word2Vec embeddings are used.
