1,721,810 research outputs found
Adapt or Perish: Algebra and Visual Notation for Service Interface Adaptation
Full text linkThe proliferation of services on the web is leading to the formation of service ecosystems wherein services interact with one another in ways not necessarily foreseen during their development or deployment. A key challenge in this setting is service mediation: the act of retrofitting existing services by intercepting, storing, transforming, and (re-)routing messages going into and out of these services so they can interact in unforeseen manners. This paper addresses a sub-problem of service mediation, namely service interface adaptation, that arises when the interface that a service provides does not match the interface that it is expected to provide in a given interaction. The paper focuses on reconciling mismatches between behavioural interfaces, i.e. interfaces that capture ordering constraints between interactions. It presents a declarative approach to service interface adaptation based on: (i) an algebra over behavioural interfaces; and (ii) a visual language that allows pairs of provided-required interfaces to be linked through algebraic expressions. These expressions are fed into an execution engine that intercepts, buffers, transforms and forwards messages to enact the adaptation logic
Schema Correspondences between Objects
No full textIn a multi-database system, schematic conflicts between two objects are usually of interest only when the objects have some semantic similarity. In this paper we try to reconcile the schematic and semantic perspectives. We introduce a uniform formalism called schema correspondences to represent structural similarities between the objects. We represent the semantic similarities between the objects using the concept of semantic proximity. We show how the reconciliation is achieved by illustrating the association of the schema correspondence(s) with and as component(s) of the semantic proximity. We also provide a data model independent semantic taxonomy on the basis of the semantic proximity defined. We then enumerate and classify the schematic and data conflicts. The association between the schema correspondences and semantic proximity helps represent the possible semantic similarities between two objects having these conflicts. One representation of uncertain information using semantic proximity as the basis is explored. Issues of inconsistent information are also discussed in the framework of semantic proximity.Technical report DCS-TR-30
Semantics-based Information Brokering: A step towards realizing the Infocosm
No full textThe rapid advances in computer and communication technologies, and their merger, is leading to a global information market place. It will consist of federations of very large number of information systems that will cooperate to varying extents to support the users' information needs. We propose an architecture which may facilitate meeting these needs. It consists of three main components: information providers, information brokers and information consumers. We also propose an approach to information brokering. We discuss two of it's tasks: information resource discovery, which identities relevant information sources for a given query, and query processing, which involves the generation of appropriate mapping from relevant but structurally heterogeneous objects. Query processing consists of information focusing and information correlation.
While the access-based search, and syntactic and hierarchical information organization has been adequate in the past, information brokering in presence of huge digital libraries or millions of information sources will likely require semantics and information-content based search and structuring of information. Our approach is based on: semantic proximity, which represents semantic similarities based on the context of comparison, and schema correspondences which are used to represent structural mappings and are associated with the context. The context of comparison of the two objects is the primary vehicle to represent the semantics for determining semantic proximity. Specifically, we use a context to capture the semantics in terms of the meaning and/or the use of an object. Using a partial context representation, we capture the assumptions in the intended use of the objects and the intended meaning of the user query. Information focusing is supported by subsequent context comparison. The same mechanism can be used to support information resource discovery. Context comparison leads to changes in schema correspondences that are used to support information correlation.Technical report DCS-TR-30
Large-scale taxonomy induction using entity and word embeddings
No full textTaxonomies are an important ingredient of knowledge organization, and serve as a backbone for more sophisticated knowledge representations in intelligent systems, such as formal ontologies. However, building taxonomies manually is a costly endeavor, and hence, automatic methods for taxonomy induction are a good alternative to build large-scale taxonomies. In this paper, we propose TIEmb, an approach for automatic unsupervised class subsumption axiom extraction from knowledge bases using entity and text embeddings. We apply the approach on the WebIsA database, a database of subsumption relations extracted from the large portion of the World Wide Web, to extract class hierarchies in the Person and Place domain
The Berlin SPARQL benchmark
No full textThe SPARQL Query Language for RDF and the SPARQL Protocol for RDF are implemented by a growing number of storage systems and are used within enterprise and open Web settings. As SPARQL is taken up by the community, there is a growing need for benchmarks to compare the performance of storage systems that expose SPARQL endpoints via the SPARQL protocol. Such systems include native RDF stores as well as systems that rewrite SPARQL queries to SQL queries against non-RDF relational databases. This article introduces the Berlin SPARQL Benchmark (BSBM) for comparing the performance of native RDF stores with the performance of SPARQL-to-SQL rewriters across architectures. The benchmark is built around an e-commerce use case in which a set of products is offered by different vendors and consumers have posted reviews about products. The benchmark query mix emulates the search and navigation pattern of a consumer looking for a product. The article discusses the design of the BSBM benchmark and presents the results of a benchmark experiment comparing the performance of four popular RDF stores (Sesame, Virtuoso, Jena TDB, and Jena SDB) with the performance of two SPARQL-to-SQL rewriters (D2R Server and Virtuoso RDF Views) as well as the performance of two relational database management systems (MySQL and Virtuoso RDBMS).</jats:p
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