Everything you always wanted to know about blank nodes

In this paper we thoroughly cover the issue of blank nodes, which have been defined in RDF as ‘existential variables’. We first introduce the theoretical precedent for existential blank nodes from first order logic and incomplete information in database theory. We then cover the different (and sometimes incompatible) treatment of blank nodes across the W3C stack of RDF-related standards. We present an empirical survey of the blank nodes present in a large sample of RDF data published on the Web (the BTC-2012 dataset), where we find that 25.7% of unique RDF terms are blank nodes, that 44.9% of documents and 66.2% of domains featured use of at least one blank node, and that aside from one Linked Data domain whose RDF data contains many “blank node cycles”, the vast majority of blank nodes form tree structures that are efficient to compute simple entailment over. With respect to the RDF-merge of the full data, we show that 6.1% of blank-nodes are redundant under simple entailment. The vast majority of non-lean cases are isomorphisms resulting from multiple blank nodes with no discriminating information being given within an RDF document or documents being duplicated in multiple Web locations. Although simple entailment is NP-complete and leanness-checking is coNP-complete, in computing this latter result, we demonstrate that in practice, real-world RDF graphs are sufficiently “rich” in ground information for problematic cases to be avoided by non-naive algorithms.     

Interpreting SWRL Rules in RDF Graphs

An unresolved issue in SWRL (the Semantic Web Rule Language) is whether the intended semantics of its RDF representation can be described as an extension of the W3C RDF semantics. In this paper we propose to make the model-theoretic semantics of SWRL compatible with RDF by interpreting SWRL rules in RDF graphs. For dealing with SWRL/RDF rules, we regard ‘Implies’ as an OWL class, and extract all ‘Implies’ rules from an RDF database that represents a SWRL knowledge base. Each ‘Implies’ rule is grounded through mappings built into the semantic conditions of the model theory. Based on the fixpoint semantics, a bottom-up strategy is employed to compute the least Herbrand models.     

Optimizing server placement in distributed systems in the presence of competition

Although the problem of data server placement in parallel and distributed systems has been studied extensively, most of the existing work assumes there is no competition between servers. Hence, their goal is to minimize read, update and storage cost. In this paper, we study the server placement problem in which a new server has to compete with existing servers for user requests. Therefore, in addition to minimizing cost, we also need to maximize the benefit of building a new server.Our major results include three parts. First, for tree-structured systems, we propose an O(|V|³k) time dynamic programming algorithm to find the optimal placement of k extra servers that maximizes the benefit in a tree with |V| nodes. We also propose an O(|V|³) time dynamic programming algorithm to find the optimal placement of extra servers that maximizes the benefit, without any constraint on the number of extra servers. Second, for general connected graphs, we prove that the server placement problems are NP-complete, and present three greedy heuristic algorithms, called Greedy Add, Greedy Remove and Greedy Add-Remove, to solve them. Third, we show that if the number of requests a server can handle (i.e., server capacity) is bounded, the server placement problem is NP-complete even for tree networks. We then derive a variation of the same set of greedy heuristic algorithms, with consideration of server capacity constraint, to solve the problem.Our experiment results demonstrate that the greedy algorithms achieve good results, when compared with the upper bounds found by a linear programming algorithm. Greedy Add performs best in the unconstrained model, yielding a benefit within 12% difference from the theoretical upper bound in average. For the constrained model, Greedy Remove performs best for smaller network sizes, while Greedy Add-Remove performs best for larger network sizes. On average, the heuristic algorithms yield a benefit within 13% difference from the theoretical upper bound in the constrained model.     

Propagation algorithms for lexicographic ordering constraints

Finite-domain constraint programming has been used with great success to tackle a wide variety of combinatorial problems in industry and academia. To apply finite-domain constraint programming to a problem, it is modelled by a set of constraints on a set of decision variables. A common modelling pattern is the use of matrices of decision variables. The rows and/or columns of these matrices are often symmetric, leading to redundancy in a systematic search for solutions. An effective method of breaking this symmetry is to constrain the assignments of the affected rows and columns to be ordered lexicographically. This paper develops an incremental propagation algorithm, GACLexLeq, that establishes generalised arc consistency on this constraint in O(n) operations, where n is the length of the vectors. Furthermore, this paper shows that decomposing GACLexLeq into primitive constraints available in current finite-domain constraint toolkits reduces the strength or increases the cost of constraint propagation. Also presented are extensions and modifications to the algorithm to handle strict lexicographic ordering, detection of entailment, and vectors of unequal length. Experimental results on a number of domains demonstrate the value of GACLexLeq.     

Simple and Efficient Minimal RDFS

The original RDFS language design includes several features that hinder the task of developers and theoreticians. This paper has two main contributions in the direction of simplifying the language. First, it introduces a small fragment which, preserving the normative semantics and the core functionalities, avoids the complexities of the original specification, and captures the main semantic functionalities of RDFS. Second, it introduces a minimalist deduction system over this fragment, which by avoiding certain rare cases, obtains a simple deductive system and a computationally efficient entailment checking.     

Contorsion: A Semantic XPath Processor

This work describes the architecture of Contorsion, a semantic XPath processor that acts over an RDF mapping of XML. It contributes to a recent research trend that defines an XML-to-RDF mapping allowing XML documents interoperate at the semantic level. We use a model-mapping approach to represent instances of XML and XML Schema in RDF. This representation retains the node order, in contrast with the usual structure-mapping approach. The processor can be fed with an unlimited set of XML schemas and/or RDFS/OWL ontologies. The queries are resolved taking in consideration the structural and semantic connections descrived in the schemas and ontologies. Such behaviour, schema-awareness and semantic integration, can be useful for exploiting schema and ontology hierarchies in XPath queries.     

Rumor spreading in social networks

Social networks are an interesting class of graphs likely to become of increasing importance in the future, not only theoretically, but also for its probable applications to ad hoc and mobile networking. Rumor spreading is one of the basic mechanisms for information dissemination in networks; its relevance stemming from its simplicity of implementation and effectiveness. In this paper, we study the performance of rumor spreading in the classic preferential attachment model of Bollobás et al. which is considered to be a valuable model for social networks. We prove that, in these networks: (a) The standard PUSH-PULL strategy delivers the message to all nodes within O(log²n) rounds with high probability; (b) by themselves, PUSH and PULL require polynomially many rounds. (These results are under the assumption that m, the number of new links added with each new node is at least 2. If m=1 the graph is disconnected with high probability, so no rumor spreading strategy can work.) Our analysis is based on a careful study of some new properties of preferential attachment graphs which could be of independent interest.     

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.     

Expressing inter-link constraints in OWL knowledge bases

Abstract: In this paper the Web Ontology Language (OWL) is examined to instantiate expert system knowledge bases intended for semantic Web applications. In particular, OWL is analyzed for expressing Unified Modeling Language (UML) representations that have been augmented with propositional logic asserted as inter‐link constraints. The motivation is ultimately to provide declarative propositional logic constraints that can be represented in UML and declaratively implemented using OWL and other constructs to realize semantic Web knowledge base repositories and databases to facilitate expert system applications. The results of this paper show that OWL is sufficient for capturing most inter‐link constraints asserted on generalization/specialization instances; however, OWL alone is inadequate for representing some inter‐link constraints asserted on associations. We propose enhancements to OWL via RDF extensions for the reification of associations into classes. These extensions mitigate all concerns that were identified in OWL as part of this study. The result is increased support of declarative constraint representations, which can be expressed in knowledge bases in the context of the semantic Web.     

nSPARQL: A navigational language for RDF

Navigational features have been largely recognized as fundamental for graph database query languages. This fact has motivated several authors to propose RDF query languages with navigational capabilities. In this paper, we propose the query language nSPARQL that uses nested regular expressions to navigate RDF data. We study some of the fundamental properties of nSPARQL and nested regular expressions concerning expressiveness and complexity of evaluation. Regarding expressiveness, we show that nSPARQL is expressive enough to answer queries considering the semantics of the RDFS vocabulary by directly traversing the input graph. We also show that nesting is necessary in nSPARQL to obtain this last result, and we study the expressiveness of the combination of nested regular expressions and SPARQL operators. Regarding complexity of evaluation, we prove that given an RDF graph G and a nested regular expression E, this problem can be solved in time O(|G||E|).     

Knowledge graph embeddings for dealing with concept drift in machine learning

Data stream learning has been largely studied for extracting knowledge structures from continuous and rapid data records. As data is evolving on a temporal basis, its underlying knowledge is subject to many challenges. Concept drift,¹ as one of core challenge from the stream learning community, is described as changes of statistical properties of the data over time, causing most of machine learning models to be less accurate as changes over time are in unforeseen ways. This is particularly problematic as the evolution of data could derive to dramatic change in knowledge. We address this problem by studying the semantic representation of data streams in the Semantic Web, i.e., ontology streams. Such streams are ordered sequences of data annotated with ontological vocabulary. In particular we exploit three levels of knowledge encoded in ontology streams to deal with concept drifts: i) existence of novel knowledge gained from stream dynamics, ii) significance of knowledge change and evolution, and iii) (in)consistency of knowledge evolution. Such knowledge is encoded as knowledge graph embeddings through a combination of novel representations: entailment vectors, entailment weights, and a consistency vector. We illustrate our approach on classification tasks of supervised learning. Key contributions of the study include: (i) an effective knowledge graph embedding approach for stream ontologies, and (ii) a generic consistent prediction framework with integrated knowledge graph embeddings for dealing with concept drifts. The experiments have shown that our approach provides accurate predictions towards air quality in Beijing and bus delay in Dublin with real world ontology streams.     

The Specification Logic νZ

This paper introduces a wide-spectrum specification logic νZ. The minimal core logic is extended to a more expressive specification logic which includes a schema calculus similar (but not equivalent) to Z, some new additional schema operators and extensions to a programming and program development logic.     

D2B: A de Bruijn based content-addressable network

We show that the de Bruijn graph is appropriate for maintaining dynamic connections, e.g., between the members of a P2P application who join and leave the system at their convenience. We describe the content-addressable network D2B, based on an overlay network preserving de Bruijn connections dynamically, and on a distributed hash table (DHT) supporting efficient publish and search procedures. The overlay network has constant expected degree, and any publish or search operation in the DHT takes a logarithmic expected number of steps.     

Browsing a document collection represented in two- and three-dimensional virtual information space

This paper reports a study of information retrieval performance using an interface in which documents were represented by objects in a virtual environment. Spatial location was determined by semantic content, with inter-object distance representing semantic similarity of documents. The quality of spatial-semantic mapping was manipulated as was the number of dimensions (two versus three) in which document nodes were arranged. Participants were required to browse the information space and identify all documents relevant to a specified topic. Results indicated that participants were able to use three-dimensional spatial mapping of semantic information to facilitate task performance, with performance being better when the quality of the mapping was higher. Strategy differences were identified, with participants adopting a more ‘exhaustive’ approach when searching two-dimensional node arrangements, and a more ‘focused’ approach for three-dimensional arrangements. Cognitive ability was not strongly associated with task performance, but participants of relatively lower cognitive ability tended to out-perform those of higher cognitive ability in three-dimensional conditions. Possible reasons for these findings are discussed.     

Web本体语言的分析与比较

本语言用于形式化描述Web文档中词汇的含义,在语义Web的7层模型中占有重要的位置。目前不同的组织提出了多种本体建模语言：RDF,RDFS,OIL,DAML OII和OWL。在介绍这些本体语言的基础上对它们进行了分析和比较,指出了它们相对某些关键特性的差异。     

Concept drift and how to identify it

This paper studies concept drift over time. We first define the meaning of a concept in terms of intension, extension and label. Then we study concept drift over time using two theories: one based on concept identity and one based on concept morphing. A qualitative toolkit for analysing concept drift is proposed to detect concept shift and stability when concept identity is available, and concept split and strength of morphing chain if using the morphing theory. We apply our framework in four case-studies: a political vocabulary in SKOS, the DBpedia ontology in RDFS, the LKIF-Core ontology in OWL and a few biomedical ontologies in OBO. We describe ways of identifying interesting changes in the meaning of concept within given application contexts. These case-studies illustrate the feasibility of our framework in analysing concept drift in knowledge organisation schemas of varying expressiveness.     

Approximation of satisfactory bisection problems

The Satisfactory Bisection problem means to decide whether a given graph has a partition of its vertex set into two parts of the same cardinality such that each vertex has at least as many neighbors in its part as in the other part. A related variant of this problem, called Co-Satisfactory Bisection, requires that each vertex has at most as many neighbors in its part as in the other part. A vertex satisfying the degree constraint above in a partition is called ‘satisfied’ or ‘co-satisfied,’ respectively. After stating the NP-completeness of both problems, we study approximation results in two directions. We prove that maximizing the number of (co-)satisfied vertices in a bisection has no polynomial-time approximation scheme (unless P=NP), whereas constant approximation algorithms can be obtained in polynomial time. Moreover, minimizing the difference of the cardinalities of vertex classes in a bipartition that (co-)satisfies all vertices has no polynomial-time approximation scheme either.     

A generalization of ACP using Belnap’s logic

ACP is combined with Belnap’s four-valued logic via conditional composition (if–then–else). We show that the operators of ACP can be seen as instances of more general, conditional operators. For example, both the choice operator + and δ (deadlock) can be seen as instances of conditional composition, and the axiom x + δ = x follows from this perspective. Parallel composition is generalized to the binary conditional merge _ψ where covers the choice between interleaving and synchronization, and ψ determines the order of execution. The instance _BB is ACP’s parallel composition, where B (both) is the truth value that models both true and false in Belnap’s logic. Other instances of this conditional merge are sequential composition, pure interleaving and synchronous merge. We investigate the expression of scheduling strategies in the conditions of the conditional merge.