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- paper-19 type InProceedings.
- paper-19 label "Towards Constructive Evidence of Data Flow-oriented Web Service Composition".
- paper-19 sameAs paper-19.
- paper-19 abstract "Automation of service composition is one of the most interesting challenges facing the Semantic Web and the Web of services today. Despite approaches which are able to infer a partial order of services, its data flow remains implicit and difficult to be automatically generated. Enhanced with formal representations, the semantic links between output and input parameters of services can be then exploited to infer their data flow. This work addresses the problem of effectively inferring data flow between services based on their representations. To this end, we introduce the non standard Description Logic reasoning join, aiming to provide a “constructive evidence” of why services can be connected and how non trivial links (many to many parameters) can be inferred in data flow. The preliminary evaluation provides evidence in favor of our approach regarding the completeness of data flow.".
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- paper-19 title "Towards Constructive Evidence of Data Flow-oriented Web Service Composition".
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- item-1 hasContent freddy-lecue.
- paper-20 type InProceedings.
- paper-20 label "The Combined Approach to OBDA: Taming Role Hierarchies using Filters".
- paper-20 sameAs paper-20.
- paper-20 abstract "The basic idea of the combined approach to query answering in the presence of ontologies is to materialize the consequences of the ontology in the data and then use a limited form of query rewriting to deal with infinite materializations. While this approach is efficient and scalable for ontologies that are formulated in the basic version of the description logic DL-Lite, it incurs an exponential blowup during query rewriting when DL-Lite is extended with the popular role hierarchies. In this paper, we show how to replace the query rewriting with a filtering technique. This is natural from an implementation perspective and allows us to handle role hierarchies without an exponential blowup. We also carry out an experimental evaluation that demonstrates the scalability of this approach.".
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- paper-20 title "The Combined Approach to OBDA: Taming Role Hierarchies using Filters".
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- item-1 hasContent carsten-lutz.
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- item-2 hasContent inanc-seylan.
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- paper-21 type InProceedings.
- paper-21 label "A snapshot of the OWL Web".
- paper-21 sameAs paper-21.
- paper-21 abstract "Tool development for and empirical experimentation in OWL ontology engineering require a wide variety of suitable ontologies as input for testing and evaluation purposes and detailed characterisations of real ontologies. Empirical activities often resort to (somewhat arbitrarily) hand curated corpora available on the web, such as the NCBO BioPortal and the TONES Repository, or manually selected sets of well-known ontologies. Findings of surveys and results of benchmarking activities may be biased, even heavily, towards these datasets. Sampling from a large corpus of ontologies, on the other hand, may lead to more representative results. Current large scale repositories and web crawls are mostly uncurated and suffer from duplication, small and (for many purposes) uninteresting ontology files, and contain large numbers of ontology versions, variants, and facets, and therefore do not lend themselves to random sampling. In this paper, we survey ontologies as they exist on the web and describe the creation of a corpus of OWL DL ontologies using strategies such as web crawling, various forms of de-duplications and manual cleaning, which allows random sampling of ontologies for a variety of empirical applications.".
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- paper-21 title "A snapshot of the OWL Web".
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- item-1 hasContent nicolas-matentzoglu.
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- paper-22 type InProceedings.
- paper-22 label "Semantic Rule Filtering for Web-Scale Relation Extraction".
- paper-22 sameAs paper-22.
- paper-22 abstract "Web-scale relation extraction is a means for building and extending large repositories of formalized knowledge. This type of automated knowledge building requires a decent level of precision, which is hard to achieve with automatically acquired rule sets learned from unlabeled data by means of distant or minimal supervision. This paper shows how precision of relation extraction can be considerably improved by employing a wide-coverage, general-purpose lexical semantic network, i.e., BabelNet, for effective semantic rule filtering. We apply Word Sense Disambiguation to the content words of the automatically extracted rules. As a result a set of relation-specific relevant concepts is obtained, and each of these concepts is then used to represent the structured semantics of the corresponding relation. The resulting relation-specific subgraphs of BabelNet are used as semantic filters for estimating the adequacy of the extracted rules. For the seven semantic relations tested here, the semantic filter consistently yields a higher precision at any relative recall value in the high-recall range.".
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- paper-22 title "Semantic Rule Filtering for Web-Scale Relation Extraction".
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- item-1 hasContent andrea-moro.
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