[PDF] Top 20 An Interpretable Knowledge Transfer Model for Knowledge Base Completion

... see, on WN18, ITransF outperforms STransE by a significant margin on rare relations. In partic- ular, in the last bin (rarest relations), the aver- age Hits@10 increases from 55.2 to 93.8, showing the great benefits of ... See full document

... dings into pairs of embeddings defined by the rela- tion and the entities’ positions within it (the left- hand-side or right-hand-side). The distances of the resulting embeddings are then compared. Socher et al. (2013) ... See full document

... statistical model, and the sec- ond step computes random walk probabilities as- sociated with each path type and node pair (these are the values in a feature ...the model relative to ... See full document

... built knowledge base completion models based on vector ...our knowledge, previous studies in this field do not target sense vectors of concepts for cross-lingual knowl- edge ... See full document

... The model we propose in this paper is termed “locality-expanded neural embedding with attention”, or LENA, since the “locality” of modelling is ex- panded from the edge level to a larger graph neighbourhood and an ... See full document

... baseline model that does not model all interactions between el- ements in a triple performs surprisingly well on both KBC and reranking when we focus on novel ... See full document

... for knowledge base completion, with progressive im- provement from the initial TransE, TransH, DistMult et al to the current state-of-the-art ...to model knowledge graphs. The ... See full document

... capture knowledge that is rarely made explicit in ...common-sense knowledge that is obvious to people such as, for instance, that bananas are yellow or that humans breath are rarely (or never) made explicit ... See full document

... the model once with the whole data set and does not involve any additional training ...trained model with known ...our knowledge this is the first paper that is focused on trying to use path ranking ... See full document

... commonsense knowledge base completion (Li et ...edge base, evaluating the model’s performance on a held-out test set from the same ...sense knowledge, to train and validate their mod- ... See full document

... Knowledge Base Completion Much of precious work in KB completion has focused on the problem of relation ...Embedding Model Weston et ...embedding model and applied it to image ... See full document

... constitutes knowledge transfer, and consequently focus on a limited range of activities and ...of knowledge transfer to be measured: (i) is strongly inspired by the proprietary model of ... See full document

... • Evaluating the proposed models through link prediction tasks for standard datasets: It is shown that our model outperforms most state-of-the-art knowledge graph embedding models for the HITS@n and MRR ... See full document

... One of their experiments is conducted as fol- lows: Given two models, one of which is known to be better (e.g., to have higher accuracy), in- stances are chosen that are classified correctly by both models. Visual ... See full document

... Finally, we re-train a ComplEx model with similar re- lations from VerbOcean (final row). When combining the datasets, we find that setting the dimension of embeddings larger to n = 100 leads to better ... See full document

... biggest difference between our model and the existing frameworks is the controller and the use of the shared memory. We follow Shen et al. (2017) for using a controller module to dynamically perform a multi-step ... See full document

... Related to our work, new versions of PRA (Gardner et al., 2013; Gardner et al., 2014) use pre-trained vector representations of relations to alleviate its feature explosion problem—but the core mechanism continues to be ... See full document

... the model can only verify whether the triple is true or ...new knowledge with high quality, there are still prob- lems with expanding new nodes and with the ac- curacy of CKB ... See full document

... We propose a different approach to combine KB and textual evidence, where the textual relations are not part of the same graph but are treated as side evidence. In our setting, a fact does not nec- essarily consist of a ... See full document

... In this paper, we propose the context path model (CPM) which generates explanations for new facts in KBC by providing sets of context paths as supporting evidence for these triples. For example, a new triple ... See full document