Extending SPARQL with regular expression patterns (for querying RDF)

RDF is a knowledge representation language dedicated to the annotation of resources within the framework of the semantic web. Among the query languages for RDF, SPARQL allows querying RDF through graph patterns, i.e., RDF graphs involving variables. Other languages, inspired by the work in databases, use regular expressions for searching paths in RDF graphs. Each approach can express queries that are out of reach of the other one. Hence, we aim at combining these two approaches. For that purpose, we define a language, called PRDF (for “Path RDF”) which extends RDF such that the arcs of a graph can be labeled by regular expression patterns. We provide PRDF with a semantics extending that of RDF, and propose a correct and complete algorithm which, by computing a particular graph homomorphism, decides the consequence between an RDF graph and a PRDF graph. We then define the PSPARQL query language, extending SPARQL with PRDF graph patterns and complying with RDF model theoretic semantics. PRDF thus offers both graph patterns and path expressions. We show that this extension does not increase the computational complexity of SPARQL and, based on the proposed algorithm, we have implemented a correct and complete PSPARQL query engine.     

Graph Grammars for Querying Graph-like Data

Recently research has deeply investigated the problem of querying semi-structured data and data which can be represented by means of graphs (e.g. object-oriented data, XML data, etc.). Typically queries on graph-like data, called path queries, are expressed by means of regular expressions denoting paths in the graph. The result of a path query is the set of nodes reachable by means of a path expressed by a specified regular expression. In this paper we investigate the problem of extracting a subgraph satisfying a given property from a given graph representing some information. We propose a new form of queries, called graph queries, whose answers are (marked) graphs having a particular structure, extracted from the source graph. We show that a simple form of graph grammars can be profitably used to define graph queries. The result of a graph query, using a grammar G over a database D, is a marked subgraph of D ‘matching’ a graph derived from G. We consider different types of graph grammars which can be used to query graph-like data and consider their expressiveness and complexity.     

Isolation concepts for efficiently enumerating dense subgraphs

In an undirected graph G=(V,E), a set of k vertices is called c-isolated if it has less than ck outgoing edges. Ito and Iwama [H. Ito, K. Iwama, Enumeration of isolated cliques and pseudo-cliques, ACM Transactions on Algorithms (2008) (in press)] gave an algorithm to enumerate all c-isolated maximal cliques in O(4^cc⁴|E|) time. We extend this to enumerating all maximal c-isolated cliques (which are a superset) and improve the running time bound to O(2.89^cc²|E|), using modifications which also facilitate parallelizing the enumeration. Moreover, we introduce a more restricted and a more general isolation concept and show that both lead to faster enumeration algorithms. Finally, we extend our considerations to s-plexes (a relaxation of the clique notion), providing a W[1]-hardness result when the size of the s-plex is the parameter and a fixed-parameter algorithm for enumerating isolated s-plexes when the parameter describes the degree of isolation.     

Processing SPARQL queries over distributed RDF graphs

We propose techniques for processing SPARQL queries over a large RDF graph in a distributed environment. We adopt a “partial evaluation and assembly” framework. Answering a SPARQL query Q is equivalent to finding subgraph matches of the query graph Q over RDF graph G. Based on properties of subgraph matching over a distributed graph, we introduce local partial match as partial answers in each fragment of RDF graph G. For assembly, we propose two methods: centralized and distributed assembly. We analyze our algorithms from both theoretically and experimentally. Extensive experiments over both real and benchmark RDF repositories of billions of triples confirm that our method is superior to the state-of-the-art methods in both the system’s performance and scalability.     

Constant-Degree Graph Expansions that Preserve Treewidth

Many hard algorithmic problems dealing with graphs, circuits, formulas and constraints admit polynomial-time upper bounds if the underlying graph has small treewidth. The same problems often encourage reducing the maximal degree of vertices to simplify theoretical arguments or address practical concerns. Such degree reduction can be performed through a sequence of splittings of vertices, resulting in an expansion of the original graph. We observe that the treewidth of a graph may increase dramatically if the splittings are not performed carefully. In this context we address the following natural question: is it possible to reduce the maximum degree to a constant without substantially increasing the treewidth?We answer the above question affirmatively. We prove that any simple undirected graph G=(V,E) admits an expansion G′=(V′,E′) with the maximum degree ≤3 and tw(G′)≤tw(G)+1, where tw(?) is the treewidth of a graph. Furthermore, such an expansion will have no more than 2|E|+|V| vertices and 3|E| edges; it can be computed efficiently from a tree-decomposition of G. We also construct a family of examples for which the increase by 1 in treewidth cannot be avoided.     

Regular path queries under approximate semantics

We give a general framework for approximate query processing in semistructured databases. We focus on regular path queries, which are the integral part of most of the query languages for semistructured databases. To enable approximations, we allow the regular path queries to be distorted. The distortions are expressed in the system by using weighted regular expressions, which correspond to weighted regular transducers. After defining the notion of weighted approximate answers we show how to compute them in order of their proximity to the query. In the new approximate setting, query containment has to be redefined in order to take into account the quantitative proximity information in the query answers. For this, we define the approximate containment, and its variants k-containment and reliable contain-ment. Then, we give an optimal algorithm for deciding the k-containment. Regarding the reliable approximate containment, we show that it is polynomial time equivalent to the notorious limitedness problem in distance automata.     

Mathematical models and routing algorithms for CAD technological preparation of cutting processes

Resource-conscious technologies for cutting sheet material include the ICP and ECP technologies that allow for aligning fragments of the contours of cutouts. In this work, we show the mathematical model for the problem of cutting out parts with these technologies and algorithms for finding cutting tool routes that satisfy technological constraints. We give a solution for the problem of representing a cutting plan as a plane graph G = (V,F,E), which is a homeomorphic image of the cutting plan. This has let us formalize technological constraints on the trajectory of cutting the parts according to the cutting plan and propose a series of algorithms for constructing a route in the graph G = (V,F,E), which is an image of an admissible trajectory. Using known coordinates of the preimages of vertices of graph G = (V,F,E) and the locations of fragments of the cutting plan that are preimages of edges of graph G = (V,F,E), the resulting route in the graph G = (V,E) can be interpreted as the cutting tool’s trajectory.The proposed algorithms for finding routes in a connected graph G have polynomial computational complexity. To find the optimal route in an unconnected graph G, we need to solve, for every dividing face f of graph G, a travelling salesman problem on the set of faces incident to f.     

Bidirectional edges problem: Part I—A simple algorithm

The bidirectional edges problem is to find an edge-labeling of an undirected network,G=(V, E), with a source and a sink, such that an edge [u, v] E is labeled (u, v) or (v, u) (or both) depending on the existence of a (simple) path from the source to sink that visits the verticesu andv, in the orderu, v orv, u, respectively. We provide several algorithms for this problem in the current paper and the sequel. In this paper we show the relation between this problem and the classical two-vertex-disjoint-paths problem and then devise a simple algorithm with a time complexity ofO(|E|·|V|²). In the sequel we improve the time complexity toO(|E|·|V|). The main technique exploits aclever partition of the graph into a set of paths and bridges which are then analyzed recursively.The bidirectional edges problem arises naturally in the context of the simulation of an MOS transistor network, in which a transistor may operate as a unilateral or a bilateral device, depending on the voltages at its source and drain nodes. For efficient simulation, it is required to detect the set of transistors that may operate as bilateral devices. Also, sometimes it is intended to propagate information in one direction only, and propagation in the wrong direction (resulting in asneak path) can cause functional error. Our algorithms can be used to detect all the sneak paths.This research was supported in part by National Science Foundation Grants DMS-8703458 and CCR-9002819.     

Enhanced algorithms for Local Search

Let G=(V,E) be a finite graph, and be any function. The Local Search problem consists in finding a local minimum of the function f on G, that is a vertex v such that f(v) is not larger than the value of f on the neighbors of v in G. In this note, we first prove a separation theorem slightly stronger than the one of Gilbert, Hutchinson and Tarjan for graphs of constant genus. This result allows us to enhance a previously known deterministic algorithm for Local Search with query complexity , so that we obtain a deterministic query complexity of , where n is the size of G, d is its maximum degree, and g is its genus. We also give a quantum version of our algorithm, whose query complexity is of . Our deterministic and quantum algorithms have query complexities respectively smaller than the algorithm Randomized Steepest Descent of Aldous and Quantum Steepest Descent of Aaronson for large classes of graphs, including graphs of bounded genus and planar graphs.     

Existence and efficient construction of fast Fourier transforms on supersolvable groups

The linear complexityL _K(A) of a matrixA over a fieldK is defined as the minimal number of additions, subtractions and scalar multiplications sufficient to evaluateA at a generic input vector. IfG is a finite group andK a field containing a primitive exp(G)-th root of unity,L _K(G):= min{L _K(A)|A a Fourier transform forKG} is called theK-linear complexity ofG. We show that every supersolvable groupG has amonomial Fourier Transform adapted to a chief series ofG. The proof is constructive and gives rise to an efficient algorithm with running timeO(|G|²log|G|). Moreover, we prove that these Fourier transforms are efficient to evaluate:L _K(G)8.5|G|log|G| for any supersolvable groupG andL _K(G)1.5|G|log|G| for any 2-groupG.     

KGDB:统一模型和语言的知识图谱数据库管理系统

知识图谱是人工智能的重要基石,其目前主要有RDF图和属性图两种数据模型,在这两种数据模型之上有数种查询语言.RDF图上的查询语言为SPARQL,属性图上的查询语言主要为Cypher.10年来,各个社区开发了分别针对RDF图和属性图的不同数据管理方法,不统一的数据模型和查询语言限制了知识图谱的更广泛应用.KGDB(kno...     

A constraint programming approach to cutset problems

We consider the problem of finding a cutset in a directed graph G=(V,E)$G=(V,E)$, i.e., a set of vertices that cuts all cycles in G  . Finding a cutset of minimum cardinality is NP-hard. There exist several approximate and exact algorithms, most of them using graph reduction techniques. In this paper, we propose a constraint programming approach to cutset problems and design a global constraint for computing cutsets. This cutset constraint is a global constraint over boolean variables associated to the vertices of a given graph and states that the subgraph restricted to the vertices having their boolean variable set to true is acyclic. We propose a filtering algorithm based on graph contraction operations and inference of simple boolean constraints, that has a linear time complexity in O(|E|+|V|)$O(|E|+|V|)$. We discuss search heuristics based on graph properties provided by the cutset constraint, and show the efficiency of the cutset constraint on benchmarks of the literature for pure minimum cutset problems, and on an application to log-based reconciliation problems where the global cutset constraint is mixed with other boolean constraints.     

A Faster Algorithm for Computing the Principal Sequence of Partitions of a Graph

We consider the following problem: given an undirected weighted graph G=(V,E,c) with nonnegative weights, minimize function c(δ(Π))−λ|Π| for all values of parameter λ. Here Π is a partition of the set of nodes, the first term is the cost of edges whose endpoints belong to different components of the partition, and |Π| is the number of components. The current best known algorithm for this problem has complexity O(|V|²) maximum flow computations. We improve it to |V| parametric maximum flow computations. We observe that the complexity can be improved further for families of graphs which admit a good separator, e.g. for planar graphs.     

Max-Stretch Reduction for Tree Spanners

A tree t-spanner T of a graph G is a spanning tree of G whose max-stretch is t, i.e., the distance between any two vertices in T is at most t times their distance in G. If G has a tree t-spanner but not a tree (t−1)-spanner, then G is said to have max-stretch of t. In this paper, we study the Max-Stretch Reduction Problem: for an unweighted graph G=(V,E), find a set of edges not in E originally whose insertion into G can decrease the max-stretch of G. Our results are as follows: (i) For a ring graph, we give a linear-time algorithm which inserts k edges improving the max-stretch optimally. (ii) For a grid graph, we give a nearly optimal max-stretch reduction algorithm which preserves the structure of the grid. (iii) In the general case, we show that it is -hard to decide, for a given graph G and its spanning tree of max-stretch t, whether or not one-edge insertion can decrease the max-stretch to t−1. (iv) Finally, we show that the max-stretch of an arbitrary graph on n vertices can be reduced to s′≥2 by inserting O(n/s′) edges, which can be determined in linear time, and observe that this number of edges is optimal up to a constant.     

The labeled perfect matching in bipartite graphs

In this paper, we deal with both the complexity and the approximability of the labeled perfect matching problem in bipartite graphs. Given a simple graph G=(V,E) with |V|=2n vertices such that E contains a perfect matching (of size n), together with a color (or label) function , the labeled perfect matching problem consists in finding a perfect matching on G that uses a minimum or a maximum number of colors.     

How expressive is stratified aggregation?

We present results on the expressive power of various deductive database languages extended with stratified aggregation. We show that (1) Datalog extended with stratified aggregation cannot express a query to count the number of paths between every pair of nodes in an acyclic graph, (2) Datalog extended with stratified aggregation and arithmetic on integers (the + operator) can express allcomputable queries on ordered domains, and (3) Datalog extended with stratified aggregation and generic function symbols can express allcomputable queries (on ordered or unordered domains). Note that without stratified aggregation, the above extensions of Datalog cannot express all computable queries. We show that replacing stratified aggregation by stratified negation preserves expressiveness. We identify subclasses of the above languages that are complete (can express all, and only the, computable queries).     

The complexity of comparability graph recognition and coloring

Using the notion ofG-decomposition introduced in Golumbic [8, 9], we present an implementation of an algorithm which assigns a transitive orientation to a comparability graph inO(δ·|E|) time andO(|E|) space where δ is the maximum degree of a vertex and |E| is the number of edges. A quotient operation reducing the graph in question and preservingG-decomposition and transitive orientability is shown, and efficient solutions to a number ofNP-complete problems which reduce to polynomial time for comparability graphs are discussed.     

Approximating the Minimum Chain Completion problem

A bipartite graph G=(U,V,E) is a chain graph [M. Yannakakis, Computing the minimum fill-in is NP-complete, SIAM J. Algebraic Discrete Methods 2 (1) (1981) 77–79] if there is a bijection such that Γ(π(1))Γ(π(2))Γ(π(|U|)), where Γ is a function that maps a node to its neighbors.We give approximation algorithms for two variants of the Minimum Chain Completion problem, where we are given a bipartite graph G(U,V,E), and the goal is find the minimum set of edges F that need to be added to G such that the bipartite graph G^′=(U,V,E^′) (E^′=EF) is a chain graph.