YAGO3: A Knowledge Base from Multilingual Wikipedias

Attribute exploration is a formal concept analytical tool for knowledge discovery by interactive determination of the implications holding between a given set of attributes..

In [1] such preferences were modelled in the language of Formal Concept Analysis as follows: An attribute dependency formula (AD formula) over a set M of attributes is A ⊑ B, where A,

The article argues that policing methods from the Mandate period continued after the Palestine force was disbanded in 1948, both within Israel and in other parts of the British

In this work, we propose an approach to predict Wikipedia infobox types by us- ing word embeddings on categories of Wikipedia articles, and analyze the impact of using

This structural mapping may be declaratively augmented by domain- specific semantics, and lifts a software design pattern highly suitable for large-scale IoT applications to

In this paper, we present a novel approach to predict Wikipedia infobox types by using word embeddings on the text present in theTable of Contents(TOC), the article’s abstract,

The entity label is submitted as a search query to a general search engine and the top ranked documents are used to add context to the ranking process.. The ranking model identifies

The article is structured as follows: In Section 2 we give short introductions to attribute exploration in the crisp setting, fuzzy sets and fuzzy logic, formal fuzzy concept