activity
20142022
most citedEnriching a Fashion Knowledge Graph from Product Textual Descriptions

3 citations · 9 across the 5 of their papers we have counts for

collaborators

5 papers

cs.AI2022

Swift Markov Logic for Probabilistic Reasoning on Knowledge Graphs

Luigi Bellomarini, Eleonora Laurenza, Emanuel Sallinger +1

We provide a framework for probabilistic reasoning in Vadalog-based Knowledge Graphs (KGs), satisfying the requirements of ontological reasoning: full recursion, powerful existenti…

cs.IR2022★ 3 cited

Enriching a Fashion Knowledge Graph from Product Textual Descriptions

João Barroca, Abhishek Shivkumar, Beatriz Quintino Ferreira +2

Knowledge Graphs offer a very useful and powerful structure for representing information, consequently, they have been adopted as the backbone for many applications in e-commerce s…

cs.DB2018★ 2 cited

Data Science with Vadalog: Bridging Machine Learning and Reasoning

Luigi Bellomarini, Ruslan R. Fayzrakhmanov, Georg Gottlob +7

Following the recent successful examples of large technology companies, many modern enterprises seek to build knowledge graphs to provide a unified view of corporate knowledge and…

cs.LO2015★ 3 cited

Containment for Conditional Tree Patterns

Alessandro Facchini, Yoichi Hirai, Maarten Marx +1

A Conditional Tree Pattern (CTP) expands an XML tree pattern with labels attached to the descendant edges. These labels can be XML element names or Boolean CTPs. The meaning of a d…

cs.DB2014★ 1 cited

High-Level Why-Not Explanations using Ontologies

Balder ten Cate, Cristina Civili, Evgeny Sherkhonov +1

We propose a novel foundational framework for why-not explanations, that is, explanations for why a tuple is missing from a query result. Our why-not explanations leverage concepts…