For centuries, sheet music scores have been the traditional way to preserve and disseminate Western music works. Nowadays, their content can be encoded in digital formats, making possible to store music score data in ...
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For centuries, sheet music scores have been the traditional way to preserve and disseminate Western music works. Nowadays, their content can be encoded in digital formats, making possible to store music score data in digital score libraries (DSL). To supply intelligent services (extracting and analysing relevant information from data), the new generation of DSL has to rely on digital representations of the score content as structured objects apt at being manipulated by high-level operators. In the present paper, we propose the Muster model, a graph -based data model for representing the music content of a digital score, and we discuss the querying of such data through graph pattern queries. We then present a proof -of -concept of this approach, which allows storing graph -based representations of music scores in the Neo4j database, and performing musical pattern searches through graph pattern queries with the Cypher query language. A benchmark study, using (real) datasets stemming from the NEUMA Digital Score Library, complements this implementation.
It is increasingly common to find graphs in which edges are of different types, indicating a variety of relation- ships. For such graphs we propose a class of reachability queries and a class of graphpatterns, in whi...
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It is increasingly common to find graphs in which edges are of different types, indicating a variety of relation- ships. For such graphs we propose a class of reachability queries and a class of graphpatterns, in which an edge is specified with a regular expression of a certain form, ex- pressing the connectivity of a data graph via edges of var- ious types. In addition, we define graphpattern matching based on a revised notion of graph simulation. On graphs in emerging applications such as social networks, we show that these queries are capable of finding more sensible informa- tion than their traditional counterparts. Better still, their in- creased expressive power does not come with extra complex- ity. Indeed, （1） we investigate their containment and mini- mization problems, and show that these fundamental prob- lems are in quadratic time for reachability queries and are in cubic time for patternqueries. （2） We develop an algorithm for answering reachability queries, in quadratic time as for their traditional counterpart. （3） We provide two cubic-time algorithms for evaluating graph pattern queries, as opposed to the NP-completeness of graphpattern matching via subgraph isomorphism. （4） The effectiveness and efficiency of these al- gorithms are experimentally verified using real-life data and synthetic data.
Answering queries using views has proven effective for querying relational and semistructured data. This paper investigates this issue for graph pattern queries based on graph simulation. We propose a notion of patter...
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Answering queries using views has proven effective for querying relational and semistructured data. This paper investigates this issue for graph pattern queries based on graph simulation. We propose a notion of pattern containment to characterize graphpattern matching using graphpattern views. We show that a pattern query can be answered using a set of views if and only if it is contained in the views. Based on this characterization, we develop efficient algorithms to answer graph pattern queries. We also study problems for determining (minimal, minimum) containment of patternqueries. We establish their complexity (from cubic-time to NP-complete) and provide efficient checking algorithms (approximation when the problem is intractable). In addition, when a pattern query is not contained in the views, we study maximally contained rewriting to find approximate answers;we show that it is in cubic-time to compute such rewriting, and present a rewriting algorithm. We experimentally verify that these methods are able to efficiently answer patternqueries on large real-world graphs.
Answering queries using views has proven effective for querying relational and semistructured data. This paper investigates this issue for graph pattern queries based on graph simulation. We propose a notion of patter...
详细信息
Answering queries using views has proven effective for querying relational and semistructured data. This paper investigates this issue for graph pattern queries based on graph simulation. We propose a notion of pattern containment to characterize graphpattern matching using graphpattern views. We show that a pattern query can be answered using a set of views if and only if it is contained in the views. Based on this characterization, we develop efficient algorithms to answer graph pattern queries. We also study problems for determining (minimal, minimum) containment of patternqueries. We establish their complexity (from cubic-time to NP-complete) and provide efficient checking algorithms (approximation when the problem is intractable). In addition, when a pattern query is not contained in the views, we study maximally contained rewriting to find approximate answers;we show that it is in cubic-time to compute such rewriting, and present a rewriting algorithm. We experimentally verify that these methods are able to efficiently answer patternqueries on large real-world graphs.
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