Compression de vocabulaire de sens grâce aux relations sémantiques pour la désambiguïsation lexicale (Sense Vocabulary Compression through Semantic Knowledge for Word Sense Disambiguation)
- Computer Science, PhilosophyJEPTALNRECITAL
Nos méthodes permettent de réduire considérablement the taille des modèles de DL neuronaux, avec l’avantage d’améliorer leur couverture sans données supplémentaires, and sans impacter leur précision.
A hybrid genetic-ant colony optimization algorithm for the word sense disambiguation problem
- Computer ScienceInf. Sci.
A graph-based approach to word sense disambiguation. An unsupervised method based on semantic relatedness
- Computer Science2016 24th Iranian Conference on Electrical Engineering (ICEE)
A new method of combining similarity metrics that uses higher order relations between words to assign appropriate weights to each edge in the graph is introduced and a new approach for selecting the most appropriate sense of the target word that makes use of the in-degree centrality algorithm and senses of the neighbor words is proposed.
Evaluating the word-expert approach for Named-Entity Disambiguation
- Computer Science, PsychologyArXiv
The results of the word-expert approach to NED are presented, where one classifier is built for each target entity mention string, as well as a study of the differences between WSD and NED, including ambiguity and synonymy statistics.
Unsupervised Word Sense Disambiguation Using Markov Random Field and Dependency Parser
- Computer ScienceAAAI
This work model the WSD problem as a Maximum A Posteriori (MAP) Inference Query on a Markov Random Field (MRF) built using WordNet and Link Parser or Stanford Parser, and their combination of dependency and MRF is novel.
Unsupervised similarity-based word sense disambiguation using context vectors and sentential word importance
- Computer ScienceTSLP
A new unsupervised similarity-based word sense disambiguation (WSD) algorithm that operates by computing the semantic similarity between glosses of the target word and a context vector, which enables it to utilize a higher degree of semantic information.
Significance of Novel WSD Algorithms
- Computer ScienceJ. Quant. Linguistics
The strong POS + Frequency baseline is proposed as a basic easy-to-implement platform for testing how well algorithms can do when combined with other high-accuracy modules, and it is shown that significant and interesting algorithms exist.
Coarse Word-Sense Disambiguation Using Common Sense
- Computer ScienceAAAI Fall Symposium: Commonsense Knowledge
This work has created a system for coarse word sense disambiguation using blending, a common sense reasoning technique, to combine information from SemCor, WordNet, ConceptNet and Extended WordNet to create a correct sense within that space.
Using Sense Clustering for the Disambiguation of Words (pp. 23-28)
- Computer SciencePolibits
The underlying idea is that the clustering of word senses provides a useful way to discover semantically related senses and this proposal regarding both fine- and coarse-grained disambiguation is evaluated.
Kernel Methods for Minimally Supervised WSD
- Computer ScienceCL
A combination of basic kernel functions are used to independently estimate syntagmatic and domain similarity, building a set of word-expert classifiers that share a common domain model acquired from a large corpus of unlabeled data.
SHOWING 1-2 OF 2 REFERENCES
WordNet : an electronic lexical database
- Computer Science
The lexical database: nouns in WordNet, Katherine J. Miller a semantic network of English verbs, and applications of WordNet: building semantic concordances are presented.