in this paper, a state-of-the-art neuron mathematical model of neural tensor network (ntn) is proposed to rdf knowledge base completion problem. one of the difficulties with the parameter of the network is that representation of its neuron mathematical model is not possible. for this reason, a new representation of this network is suggested that solves this difficulty. in the representation, th...

This paper introduces knowledgebase approximation and fusion using association rule aggregation as a means to facilitate accelerated insight induction from high-dimensional disparate knowledgebases. There are two typical observations that make approximating knowledgebases of interest: (1) It is quite often insights can be derived based partial set the samples, not necessarily all them; (2) gene...

Increasing efforts are being dedicated towards improving cancer care via personalized medicine. These efforts depend to a large degree on the availability of a knowledge foundation. Unfortunately, existing knowledge linking cancer drugs and potential efficacy biomarkers is in its infancy; and where links are known, they are frequently unstructured and poorly documented. We have developed a new ...

A common assumption for logic-based argumentation is that an argument is a pair 〈Φ, α〉 where Φ is a minimal subset of the knowledgebase such that Φ is consistent and Φ entails the claim α. Different logics are based on different definitions for entailment and consistency, and these give us different options for argumentation. For a variety of logics, in particular for classical logic, there is ...

The task of creating a lexical knowledgebase has been defined in our work as extracting appropriate semantic phenomena from what are essentially print dictionaries stored in a desktop publishing format. The aim of this work is to achieve automatic identification of structural elements in the dictionaryy’s stream of text that are isomorphic to semantic fields of interest. A fully automatic solut...

Embedding-based Knowledge Base Completion models have so far mostly combined distributed representations of individual entities or relations to compute truth scores of missing links. Facts can however also be represented using pairwise embeddings, i.e. embeddings for pairs of entities and relations. In this paper we explore such bigram embeddings with a flexible Factorization Machine model and ...

There have been a number of proposals for measuring inconsistency in a knowledgebase (i.e. a set of logical formulae). These include measures that consider the minimally inconsistent subsets of the knowledgebase, and measures that consider the paraconsistent models (3 or 4 valued models) of the knowledgebase. In this paper, we present a new approach that considers the amount each formula has to...

As an increasing number of applications on the web contain some elements of spatial data, there is a need to efficiently integrate Semantic Web technologies and spatial data processing. This paper describes a prototype system for storing spatial data and Semantic Web data together in a SPatiallyAUgmented Knowledgebase (SPAUK) without sacrificing query efficiency. The goals are motivated through...