Search Results for author:
Found 13 papers, 3 papers with code
Assessing Wordnets with WordNet Embeddings
An effective conversion method was proposed in the literature to obtain a lexical semantic space from a lexical semantic graph, thus permitting to obtain WordNet embeddings from WordNets.
WordnetLoom – a Multilingual Wordnet Editing System Focused on Graph-based Presentation
The paper presents a new re-built and expanded, version 2. 0 of WordnetLoom – an open wordnet editor.
Large Scale Author Obfuscation Using Siamese Variational Auto-Encoder: The SiamAO System
Author obfuscation is the task of masking the author of a piece of text, with applications in privacy.
Comparative Probing of Lexical Semantics Theories for Cognitive Plausibility and Technological Usefulness
Lexical semantics theories differ in advocating that the meaning of words is represented as an inference graph, a feature mapping or a vector space, thus raising the question: is it the case that one of these approaches is superior to the others in representing lexical semantics appropriately?
The MWN.PT WordNet for Portuguese: Projection, Validation, Cross-lingual Alignment and Distribution
The objective of the present paper is twofold, to present the MWN. PT WordNet and to report on its construction and on the lessons learned with it.
Siamese Networks for Large-Scale Author Identification
Authorship attribution is the process of identifying the author of a text.
Whom to Learn From? Graph- vs. Text-based Word Embeddings
Vectorial representations of meaning can be supported by empirical data from diverse sources and obtained with diverse embedding approaches.
Predicting Brain Activation with WordNet Embeddings
The task of taking a semantic representation of a noun and predicting the brain activity triggered by it in terms of fMRI spatial patterns was pioneered by Mitchell et al. 2008.
WordNet Embeddings
Semantic networks and semantic spaces have been two prominent approaches to represent lexical semantics.
Ways of Asking and Replying in Duplicate Question Detection
This paper presents the results of systematic experimentation on the impact in duplicate question detection of different types of questions across both a number of established approaches and a novel, superior one used to address this language processing task.
