Cristian Riveros

Querying Wikidata: Comparing SPARQL, Relational and Graph Databases

In this paper, we experimentally compare the efficiency of various database engines for the purposes of querying the Wikidata knowledge-base, which can be conceptualised as a directed edge-labelled graph where edges can be annotated with meta-information called qualifiers. We take two popular SPARQL databases (Virtuoso, Blazegraph), a popular relational database (PostgreSQL), and a popular graph database (Neo4J) for comparison and discuss various options as to how Wikidata can be represented in the models of each engine. We design a set of experiments to test the relative query performance of these representations in the context of their respective engines. We first execute a large set of atomic lookups to establish a baseline performance for each test setting, and subsequently perform experiments on instances of more complex graph patterns based on real-world examples. We conclude with a summary of the strengths and limitations of the engines observed.

The per-character cost of repairing word languages

We show how to calculate the maximum number of edits per character needed to convert any string in one regular language to a string in another language. Our algorithm makes use of a local determinization procedure applicable to a subclass of distance automata. We then show how to calculate the same property when the editing needs to be done in streaming fashion, by a finite state transducer, using a reduction to mean-payoff games. In this case, we show that the optimal streaming editor can be produced in P.

A framework for annotating CSV-like data

In this paper, we propose a simple and expressive framework for adding metadata to CSV documents and their noisy variants. The framework is based on annotating parts of the document that can be later used to read, query, or exchange the data. The core of our framework is a language based on extended regular expressions that are used for selecting data. These expressions are then combined using a set of rules in order to annotate the data. We study the computational complexity of implementing our framework and present an efficient evaluation algorithm that runs in time proportional to its output and linear in its input. As a proof of concept, we test an implementation of our framework against a large number of real world datasets and show that it can be efficiently used in practice.

Maximal Partition Logic: Towards a Logical Characterization of Copyless Cost Register Automata

It is highly desirable for a computational model to have a logic characterization like in the seminal work from Buchi that connects MSO with finite automata. For example, weighted automata are the quantitative extension of finite automata for computing functions over words and they can be naturally characterized by a subframent of weighted logic introduced by Droste and Gastin. Recently, cost register automata (CRA) were introduced by Alur et al. as an alternative model for weighted automata. In hope of finding decidable subclasses of weighted automata, they proposed to restrict their model with the so-called copyless restriction. Unfortunately, copyless CRA do not enjoy good closure properties and, therefore, a logical characterization of this class seems to be unlikely. n nIn this paper, we introduce a new logic called maximal partition logic (MPL) for studying the expressiveness of copyless CRA. In contrast from the previous approaches (i.e. weighted logics), MPL is based on a new set of regular quantifiers that partition a word into maximal subwords, compute the output of a subformula over each subword separately, and then aggregate these outputs with a semiring operation. We study the expressiveness of MPL and compare it with weighted logics. Furthermore, we show that MPL is equally expressive to a natural subclass of copyless CRA. This shows the first logical characterization of copyless CRA and it gives a better understanding of the copyless restriction in weighted automata.

Document Spanners for Extracting Incomplete Information: Expressiveness and Complexity

Rule-based information extraction has lately received a fair amount of attention from the database community, with several languages appearing in the last few years. Although information extraction systems are intended to deal with semistructured data, all language proposals introduced so far are designed to output relations, thus making them incapable of handling incomplete information. To remedy the situation, we propose to extend information extraction languages with the ability to use mappings, thus allowing us to work with documents which have missing or optional parts. Using this approach, we simplify the semantics of regex formulas and extraction rules, two previously defined methods for extracting information. We extend them with the ability to handle incomplete data, and study how they compare in terms of expressive power. We also study computational properties of these languages, focusing on the query enumeration problem, as well as satisfiability and containment.

Copyless cost-register automata: Structure, expressiveness, and closure properties

Abstract Cost register automata (CRA) and its subclass, copyless CRA, were recently proposed by Alur et al. as a new model for computing functions over strings. We study some structural properties, expressiveness, and closure properties of copyless CRA. We show that copyless CRA are strictly less expressive than weighted automata and are not closed under reverse operation. To find a better class we impose restrictions on copyless CRA, which ends successfully with a new robust computational model that is closed under reverse and other extensions.

Descriptive Complexity for counting complexity classes

Descriptive Complexity has been very successful in characterizing complexity classes of decision problems in terms of the properties definable in some logics. However, descriptive complexity for counting complexity classes, such as FP and #P, has not been systematically studied, and it is not as developed as its decision counterpart. In this paper, we propose a framework based on Weighted Logics to address this issue. Specifically, by focusing on the natural numbers we obtain a logic called Quantitative Second Order Logics (QSO), and show how some of its fragments can be used to capture fundamental counting complexity classes such as FP, #P and FPSPACE, among others. We also use QSO to define a hierarchy inside #P, identifying counting complexity classes with good closure and approximation properties, and which admit natural complete problems. Finally, we add recursion to QSO, and show how this extension naturally captures lower counting complexity classes such as #L.

Copyless Cost-Register Automata: Structure, Expressiveness, and Closure Properties.

Cost register automata (CRA) and its subclass, copyless CRA, were recently proposed by Alur et al. as a new model for computing functions over strings. We study structural properties, expressiveness, and closure properties of copyless CRA. We show that copyless CRA are strictly less expressive than weighted automata and are not closed under reverse operation. To find a better class we impose restrictions on copyless CRA, which ends successfully with a new robust computational model that is closed under reverse and other extensions.

Constant Delay Algorithms for Regular Document Spanners

Regular expressions and automata models with capture variables are core tools in rule-based information extraction. These formalisms, also called regular document spanners, use regular languages in order to locate the data that a user wants to extract from a text document, and then store this data into variables. Since document spanners can easily generate large outputs, it is important to have good evaluation algorithms that can generate the extracted data in a quick succession, and with relatively little precomputation time. Towards this goal, we present a practical evaluation algorithm that allows constant delay enumeration of a spanners output after a precomputation phase that is linear in the document. While the algorithm assumes that the spanner is specified in a syntactic variant of variable set automata, we also study how it can be applied when the spanner is specified by general variable set automata, regex formulas, or spanner algebras. Finally, we study the related problem of counting the number of outputs of a document spanner, providing a fine grained analysis of the classes of document spanners that support efficient enumeration of their results.

Bounded Repairability for Regular Tree Languages

We study the problem of bounded repairability of a given restriction tree language R into a target tree language T. More precisely, we say that R is bounded repairable with respect to T if there exists a bound on the number of standard tree editing operations necessary to apply to any tree in R to obtain a tree in T. We consider a number of possible specifications for tree languages: bottom-up tree automata (on curry encoding of unranked trees) that capture the class of XML schemas and document type definitions (DTDs). We also consider a special case when the restriction language R is universal (i.e., contains all trees over a given alphabet).n We give an effective characterization of bounded repairability between pairs of tree languages represented with automata. This characterization introduces two tools—synopsis trees and a coverage relation between them—allowing one to reason about tree languages that undergo a bounded number of editing operations. We then employ this characterization to provide upper bounds to the complexity of deciding bounded repairability and show that these bounds are tight. In particular, when the input tree languages are specified with arbitrary bottom-up automata, the problem is coNExp-complete. The problem remains coNExp-complete even if we use deterministic nonrecursive DTDs to specify the input languages. The complexity of the problem can be reduced if we assume that the alphabet, the set of node labels, is fixed: the problem becomes PSpace-complete for nonrecursive DTDs and coNP-complete for deterministic nonrecursive DTDs. Finally, when the restriction tree language R is universal, we show that the bounded repairability problem becomes Exp-complete if the target language is specified by an arbitrary bottom-up tree automaton and becomes tractable (P-complete, in fact) when a deterministic bottom-up automaton is used.