Графовая структура

We present a novel approach to weakly super- vised semantic class learning from the web, using a single powerful hyponym pattern com- bined with graph structures, which capture two properties …...

We propose a global algorithm for learn- ing entailment relations between predi- cates. We define a graph structure over predicates that represents entailment rela- tions as directed edges, and use …...

Performing link prediction in Knowledge Bases (KBs) with embedding-based mod- els, like with the model TransE (Bordes et al., 2013) which represents relationships as translations in the embedding space, have …...

AbstractGeneral treebank analyses are graph structured, but parsers are typically restricted to tree structures for efficiency and modeling reasons. We propose a new representation and algorithm for a class of …...

Metaphors are not only remarkably pervasive in both informal and formal text, but reflect fundamental properties of human cognition. This paper presents an algorithmic model that suggests metaphoric means of …...

AbstractPrecisely defining the terminology is the first step in scientific communication. Developing neural text generation models for definition generation can circumvent the labor-intensity curation, further accelerating scientific discovery. Unfortunately, the …...

AbstractThe state-of-the-art models for coreference resolution are based on independent mention pair-wise decisions. We propose a modelling approach that learns coreference at the document-level and takes global decisions. For this …...

AbstractThe widespread of fake news has detrimental societal effects. Recent works model information propagation as graph structure and aggregate structural features from user interactions for fake news detection. However, they …...