Gianluca Demartini

TL;DR: Bringing humans back to the frontier of FoW will increase their trust in AI systems and shift their perception to use them as a source of self-improvement, ensure better work performance, and positively shape social and economic outcomes of a society and a nation.

TL;DR: This paper reports on the INEX 2009 evaluation campaign, which consisted of a wide range of tracks: Ad hoc, Book, Efficiency, Entity Ranking, Interactive, QA, Link the Wiki, and XML Mining.

TL;DR: This paper presents a user study in which various kinds of exploratory behavior and goals are investigated, as well as different kinds of visualizations to support exploration.

TL;DR: In this article, the authors report on an analysis of the schema adherence of domains and ranges for Linked Open Data and propose new techniques to improve the correctness of domain and range by identifying the cases in which a property is used in the data with several dierent semantics, and resolving them by updating the underlying schema and/or by modifying the data without compromising its retro compatibility.

TL;DR: In this article, the authors focus on the Wikipedia corpus and propose algorithms for finding entities based on query relaxation using category information, which is done leveraging on a highly accurate ontology which is matched to the character strings of the topic.