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IEEE International Conference on Big Data (Big Data)

作者： Mebrek, Wafaa Raddaoui, Badran Albilani, Mohamad Telecom SudParis Inst Polytech Paris CNRS SAMOVAR Paris France

ISBN: (纸本)9781728108582

Database users can be frustrated by having an empty answer to a query. In particular, querying rdf triple-stores arc prone to failure due to the nature of rdf data. The problem of query relaxation is thus a helpful technique for efficiently querying rdf databases by providing users with alternative answers instead of an empty result. The main shortcoming of most prior researches is that they focus on the relaxation itself rather than the causes of failure. Yet, determining possible explanations, i.e. diagnoses, for an unexpected behavior of the system under observation is crucial to the user. In this paper, we present CADER, a novel approach for computing relaxations for failed queries over rdf databases. We show how the number of required database queries for determining all the possible relaxations can be limited to the search of failed subqueries of the user query. Then, we point out how the hitting set problem can be applied for determining the possible relaxed queries in an efficient way without querying the rdf database. Finally, the efficiency and scalability of CADER against existing solutions are shown through extensive experiments on the well-known rdf benchmarks with a variety of queries of different shapes.

关键词： Semantic Web rdf databases Query Relaxation Hitting Set Problem

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Efficiently Evaluating Skyline Queries on rdf databases

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8th Extended Semantic Web Conference (ESWC)

作者： Chen, Ling Gao, Sidan Anyanwu, Kemafor N Carolina State Univ Dept Comp Sci Semant Comp Res Lab Raleigh NC 27695 USA

ISBN: (纸本)9783642210648

Skyline queries are a class of preference queries that compute the pareto-optimal tuples from a set of tuples and are valuable for multi-criteria decision making scenarios. While this problem has received significant attention in the context of single relational table, skyline queries over joins of multiple tables that are typical of storage models for rdf data has received much less attention. A naive approach such as a join-first-skyline-later strategy splits the join and skyline computation phases which limit opportunities for optimization. Other existing techniques for multi-relational skyline queries assume storage and indexing techniques that are not typically used with rdf which would require a preprocessing step for data transformation. In this paper, we present an approach for optimizing skyline queries over rdf data stored using a vertically partitioned schema model. It is based on the concept of a "Header Point" which maintains a concise summary of the already visited regions of the data space. This summary allows some fraction of non-skyline tuples to be pruned from advancing to the skyline processing phase, thus reducing the overall cost of expensive dominance checks required in the skyline phase. We further present more aggressive pruning rules that result in the computation of near-complete skylines in significantly less time than the complete algorithm. A comprehensive performance evaluation of different algorithms is presented using datasets with different types of data distributions generated by a benchmark data generator.

关键词： Skyline Queries rdf databases Join

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Effectively Interpreting Keyword Queries on rdf databases with a Rear View

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Semantic Web Challenge at the 10th International Semantic Web Conference

作者： Fu, Haizhou Anyanwu, Kemafor N Carolina State Univ Dept Comp Sci Semant Comp Res Lab Raleigh NC 27606 USA

ISBN: (纸本)9783642250729

Effective techniques for keyword search over rdf databases incorporate an explicit interpretation phase that maps keywords in a keyword query to structured query constructs. Because of the ambiguity of keyword queries, it is often not possible to generate a unique interpretation for a keyword query. Consequently, heuristics geared toward generating the top-K likeliest user-intended interpretations have been proposed. However, heuristics currently proposed fail to capture any user-dependent characteristics, but rather depend on database-dependent properties such as occurrence frequency of subgraph pattern connecting keywords. This leads to the problem of generating top-K interpretations that are not aligned with user intentions. In this paper, we propose a context-aware approach for keyword query interpretation that personalizes the interpretation process based on a user's query context. Our approach addresses the novel problem of using a sequence of structured queries corresponding to interpretations of keyword queries in the query history as contextual information for biasing the interpretation of a new query. Experimental results presented over DBPedia dataset show that our approach outperforms the state-of-the-art technique on both efficiency and effectiveness, particularly for ambiguous queries.

关键词： Query Interpretation Keyword Search Query Context rdf databases

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In-Memory Graph databases for Web-Scale Data

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COMPUTER 2015年第3期48卷 24-35页

作者： Castellana, Vito Giovanni Morari, Alessandro Weaver, Jesse Tumeo, Antonino Haglin, David Villa, Oreste Feo, John Pacific NW Natl Lab High Performance Comp Grp Richland WA 99352 USA Pacific NW Natl Lab Data Sci Grp Richland WA 99352 USA Pacific NW Natl Lab Data Intens Sci Comp Grp Richland WA 99352 USA

A software stack relies primarily on graph-based methods to implement scalable resource description framework databases on top of commodity clusters, providing an inexpensive way to extract meaning from volumes of het... 详细信息

关键词： Internet database management systems graph theory pattern clustering Web-scale data commodity clusters graph-based methods heterogeneous data inmemory graph databases scalable resource description framework databases software stack Algorithm design and analysis Clustering algorithms Data structures Pattern matching Resource description framework Resource management Software development rdf databases SPARQL big data graph databases high-performance computing multithreading

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On the Power of SPARQL in Expressing Navigational Queries

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COMPUTER JOURNAL 2015年第11期58卷 2841-2851页

作者： Zhang, Xiaowang Van den Bussche, Jan Univ Limburg Hasselt Univ & Transnat B-3500 Hasselt Belgium

Navigational queries on graph databases return binary relations over the nodes of the graph. The calculus of relations, popularized by Tarski, serves as a natural benchmark for first-order navigational querying. Recently, nested regular expressions (nre's) have been proposed to extend navigational querying to resource description framework graphs, i.e. ternary relations. This paper investigates the expressiveness of nre's and their relationship to basic SPARQL queries. An elegant proof is given to the effect that nre queries are already expressible as basic SPARQL queries. This result takes exception of nre's involving Kleene star (transitive closure), but on the other hand it holds even when extending nre's with negation (complementation). The resulting language of 'star-free nre's with negation (sfnre(Anot sign))' can in fact be captured by a precisely delineated fragment of SPARQL, called Tarski-SPARQL. The resulting language is also compared with an alternative extension that adds negation in the form of the difference operator. While sfnre(Anot sign) queries are subsumed by first-order logic with three variables (FO3), it is shown that some natural FO3 queries are not expressible in nre(Anot sign), even when allowing transitive closure.

关键词： rdf databases nested regular expression star-free nested regular expression complement difference Tarski-SPARQL

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Lens: A Faceted Browser for Research Networking Platforms

Lens: A Faceted Browser for Research Networking Platforms

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IEEE 9th International Conference on e-Science (e-Science)

作者： Whaling, Richard Malik, Tanu Foster, Ian Univ Chicago Computat Inst Chicago IL 60637 USA Argonne Natl Lab Computat Inst Chicago IL USA

ISBN: (纸本)9780769550831

Research networking platforms, such as VIVO and Profiles Networking provide an information infrastructure for scholarship, representing information about research and researchers-their scholarly works, research interests, and organizational relationships. These platforms are open information infrastructures for scholarship, consisting of linked open data and open-source software tools for managing and visualizing scholarly information. Being rdf based, faceted browsing is a natural technique for navigating such data, partitioning the scholarly information space into orthogonal conceptual dimensions. However, this technique has so far been explored through limited queries in research networking platforms--not allowing for instance full graph based navigation on rdf data. In this paper we present Lens a client-side user interface for faceted navigation of scholarly rdf data. Lens is based on Exhibit, which is a lightweight structured data-publishing framework, but extends Exhibit for expressive SPARQL-like queries and scales it up for navigating amounts of rdf data. Lens consumes data in VIVO ontology, the de facto schema for researcher networking systems. We show how Lens provides better usability over current faceted browsers for research networking platforms.

关键词： researcher profiling systems rdf databases faceted search ontologies user interfaces (key words)

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The LDBC Social Network Benchmark: Interactive Workload 15

The LDBC Social Network Benchmark: Interactive Workload

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ACM SIGMOD International Conference on Management of Data

作者： Erling, Orri Averbuch, Alex Larriba-Pey, Josep Chafi, Hassan Gubichev, Andrey Prat, Arnau Minh-Duc Pham Boncz, Peter OpenLink Software Croydon Surrey England Neo Technol Malmo Sweden Spars Technol Barcelona Spain Oracle Labs Belmont CA USA Tech Univ Munich Munich Germany Univ Politecn Cataluna Barcelona Spain Vrije Univ Amsterdam Amsterdam Netherlands CWI Amsterdam Netherlands

ISBN: (纸本)9781450327589

The Linked Data Benchmark Council (LDBC) is now two years underway and has gathered strong industrial participation for its mission to establish benchmarks, and benchmarking practices for evaluating graph data management systems. The LDBC introduced a new choke-point driven methodology for developing benchmark workloads, which combines user input with input from expert systems architects, which we outline. This paper describes the LDBC Social Network Benchmark (SNB), and presents database benchmarking innovation in terms of graph query functionality tested, correlated graph generation techniques, as well as a scalable benchmark driver on a workload with complex graph dependencies. SNB has three query workloads under development: Interactive, Business Intelligence, and Graph Algorithms. We describe the SNB Interactive Workload in detail and illustrate the workload with some early results, as well as the goals for the two other workloads.

关键词： benchmarking rdf databases graph databases

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Probabilistic Subgraph Matching on Huge Social Networks

Probabilistic Subgraph Matching on Huge Social Networks

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International Conference on Advances in Social Networks Analysis and Mining (ASONAM)

作者： Brocheler, Matthias Pugliese, Andrea Subrahmanian, V. S. Univ Maryland Dept Comp Sci College Pk MD 20742 USA Univ Calabria DEIS Dept Arcavacata Di Rende Italy

ISBN: (纸本)9780769543758

Users querying massive social networks or rdf databases are often not 100% certain about what they are looking for due to the complexity of the query or heterogeneity of the data. In this paper, we propose "probabilistic subgraph" ( PS) queries over a graph/network database, which afford users great flexibility in specifying "approximately" what they are looking for. We formally define the probability that a substitution satisfies a PS-query with respect to a graph database. We then present the PMATCH algorithm to answer such queries and prove its correctness. Our experimental evaluation demonstrates that PMATCH is efficient and scales to massive social networks with over a billion edges.

关键词： Indexes PMATCH algorithm Probabilistic logic rdf databases Reactive power Resource description framework Social network services Springs graph database graph theory massive social networks pattern matching probabilistic subgraph matching probability query processing social networking (online) users querying

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Multidimensional rdf

Multidimensional RDF

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OTM Confederated International Conference and Workshop

作者： Gergatsoulis, M Lilis, P Ionian Univ Dept Arch & Library Sci Corfu 49100 Greece

ISBN: (纸本)3540297383

rdf has been proposed by W3C as a metadata model and language for representing information about resources in WWW, In this paper we introduce Multidimensional rdf (or Mrdf), as an extension of rdf, suitable for representing context-dependent rdf data. In Mrdf we have a set of dimensions whose values define different contexts (or worlds) under which different parts of an rdf graph may hold, We define the semantics of Mrdf in terms of the semantics of rdf. Additionally, we propose appropriate extensions, suitable for representing Mrdf graphs in triples notation and rdf/XML syntax. Finally, we demonstrate how an Mrdf graph, embodying a single time dimension, can be used to model the history of a conventional rdf graph.

关键词： rdf databases rdf model Semantic Web versioning

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On the Primitivity of SPARQL 1.1 Operators 26

On the Primitivity of SPARQL 1.1 Operators

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26th International Conference on World Wide Web (WWW)

作者： Zhang, Xiaowang Tianjin Univ Sch Comp Sci & Technol Tianjin 300350 Peoples R China Tianjin Key Lab Cognit Comp & Applicat Tianjin 300350 Peoples R China Minist Educ Key Lab Comp Network & Informat Integrat Nanjing Peoples R China

ISBN: (纸本)9781450349147

The paper studies the primitivity of the eleven basic operators used in the SPARQL 1.1 query language. This paper shows that the six operators BIND, FILTER, GRAPH, property path, SELECT, and VALUES are primitive while the left five operators AND, EXISTS, MINUS, OPT, and UNION, are not primitive. It is surprised that OPT and UNION which are primitive in SPARQL 1.0 become no longer primitive in SPARQL 1.1.

关键词： rdf databases SPARQL 1.1 primitive operator expressive power

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