Links' Seminars and Public Events |
2020 | |
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Fri 27th Nov 10:00 am 11:30 am | Seminar: Charles Paperman Title: Stackless processing of streamed trees Abstract: In this talk, I will first present the state of the art of efficiency implementation of streaming-text algorithms on modern architecture. Then some recent results on the extraction of information on streamed of structured documents without stack overhead. For more info: paperman.name/data/pub.....d.pdf |
Fri 13th Nov 10:00 am 12:00 pm | Seminar: Mikaël Monet Title: The Complexity of Counting Problems over Incomplete Databases Abstract: In this presentation, I will talk about various counting problems that naturally arise in the context of query evaluation over incomplete databases. Incomplete databases are relational databases that can contain unknown values in the form of labeled nulls. We will assume that the domains of these unknown values are finite and, for a Boolean query $q$, we will consider the following two problems: given as input an incomplete database $D$, (a) return the number of completions of $D$ that satisfy $q$; or (b) return or the number of valuations of the nulls of $D$ yielding a completion that satisfies $q$. We will study the computational complexity of these problems when $q$ is a self-join--free conjunctive query, and study the impact on the complexity of the following two restrictions: (1) every null occurs at most once in $D$ (what is called *Codd tables*); and (2) the domain of each null is the same. Roughly speaking, we will see that counting completions is much harder than counting valuations, and that both (1) and (2) can reduce the complexity of our problems. I will also talk about the approximability of these problems and prove that, while counting valuations can efficiently be approximated, in most cases counting completions cannot. On our way, we will encounter the counting complexity classes #P, Span-P and Span-L. The presentation will be based on joint work with Marcelo Arenas and Pablo Barcelo; see arxiv.org/abs/1912.11064 |
Fri 16th Oct 11:00 am 12:00 pm | Seminar: Aurélien Lemay Title: ShEx Learning from Typed Graphs Abstract: In knowledge graphs, schemas are becoming a new asset to describe the organization of data. The new world-leading format Shex is becoming a de-facto standard in the industry that allows defining flexible and powerful schemas. In this context, the inference of schemas can become a solution to provide shex expressions that describe already existing data. Typically, the inference starts from untyped graphs. However, these tasks appears to be more complex than expected in general, and is possible only for subclasses of Shex. The inference of schemas from typed graph gives a baseline for those algorithms. Its comprehension allows to understand better the underlying difficulties of the task. It presents already unexpected difficulties. We present an algorithm that infers Shex-defined schemas from fully typed graphs. We also present some encountered difficulties, as well as the limitations of the approach. |