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      Full-text Support for Publish/Subscribe Ontology Systems

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          Abstract

          We envision a publish/subscribe ontology system that is able to index millions of user subscriptions and filter them against ontology data that arrive in a streaming fashion. In this work, we propose a SPARQL extension appropriate for a publish/subscribe setting; our extension builds on the natural semantic graph matching of the language and supports the creation of full-text subscriptions. Subsequently, we propose a main-memory subscription indexing algorithm which performs both semantic and full-text matching at low complexity and minimal filtering time. Thus, when ontology data are published matching subscriptions are identified and notifications are forwarded to users.

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          Information filtering and query indexing for an information retrieval model

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            Author and article information

            Journal
            2013-07-08
            Article
            1307.2015
            1f33944e-45b7-4b48-9746-c03a1453aec1

            http://arxiv.org/licenses/nonexclusive-distrib/1.0/

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            Custom metadata
            ESWC 2012 Demo
            cs.IR cs.DB

            Databases,Information & Library science
            Databases, Information & Library science

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