Séminaire Valda: Liat Peterfreund et Yann Ramusat

5 mars 2021, 10:30-11:30

Séminaire en ligne : https://bbb.di.ens.fr/b/cam-pz6-kdj

Grammars for Document Spanners (Liat Peterfreund)

We propose a new grammar-based language for defining information-extractors from documents (text) that is built upon the well-studied framework of Document Spanners for extracting structured data from text. While previously studied formalisms for document spanners are mainly based on regular expressions, we use an extension of context-free grammars, called extraction grammars, to define the new class of context-free spanners. Extraction grammars are simply context-free grammars extended with variables that capture interval positions of the document, namely spans. While regular expressions are efficient for tokenizing and tagging, context-free grammars are also efficient for capturing structural properties. Indeed, we show that context-free spanners are strictly more expressive than their regular counterparts. We reason about the expressive power of our new class and present a pushdown-automata model that captures it. We show that extraction grammars can be evaluated with polynomial data complexity. Nevertheless, as the degree of the polynomial depends on the query, we present an enumeration algorithm for (a subset of) extraction grammars that, after quintic preprocessing, outputs the results sequentially, without repetitions, with a constant delay between every two consecutive ones.

Provenance-Based Algorithms for Rich Queries over Graph Databases (Yann Ramusat)

In this paper, we investigate the efficient computation of the provenance of rich queries over graph databases. We show that semiring-based provenance annotations enrich the expressiveness of routing queries over graphs. Several algorithms have previously been proposed for provenance computation over graphs, each yielding a trade-off between time complexity and generality. Here, we address the limitations of these algorithms and propose a new one, partially bridging a complexity and expressiveness gap and adding to the algorithmic toolkit for solving this problem. Importantly, we provide a comprehensive taxonomy of semirings and corresponding algorithms, establishing which practical approaches are needed in different cases. We implement and comprehensively evaluate several practical applications of the problem (e.g., shortest distances, top-k shortest distances, Boolean or integer path features), each corresponding to a specific semiring and algorithm, that depends on the properties of the semiring. On several real-world and synthetic graph datasets, we show that the algorithms we propose exhibit large practical benefits for processing rich graph queries. 

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