Swoogle

Ding, Li; Finin, Tim; Joshi, Anupam; Pan, Rong; Cost, R. Scott; Peng, Yun; Reddivari, Pavan; Doshi, V. C.; Sachs, Joel

doi:10.1145/1031171.1031289

Cited by 533 publications

(33 citation statements)

References 7 publications

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“…We obtained the ontologies via Swoogle (Ding et al, ) and Watson (d'Aquin et al, ) ontology search engines to annotate the texts. We used the ontologies only represented in RDF, RDFS, and OWL.…”

Section: Experiment: Measuring Text Coherence Using An Ontology‐basedmentioning

confidence: 99%

“…Jena semantic web framework (McBride, ) was used to process ontologies. Swoogle (Ding et al, ) and Watson (d'Aquin et al, ) ontology search engines were used to find ontologies for annotating texts.…”

Section: Experiment: Measuring Text Coherence Using An Ontology‐basedmentioning

confidence: 99%

“…Therefore, we needed a wide variety of ontologies from various domains. We preferred to use ontology search engines, namely, Swoogle (Ding et al, ) and Watson (d'Aquin et al, ), to find as many ontologies as possible. A disadvantage of using search engines is the time required to search and download the relevant ontologies.…”

Section: Experiment: Measuring Text Coherence Using An Ontology‐basedmentioning

confidence: 99%

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Assessment of text coherence using an ontology‐based relatedness measurement method

Giray¹,

Ünalır

2019

Expert Systems

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This paper proposes a novel method for assessing text coherence. Central to this approach is an ontology‐based representation of text, which captures the level of relatedness between consecutive sentences via ontologies. Our method encompasses annotating text using ontological concepts and assessing text coherence based on relatedness measurement among these concepts. The ontology‐based relatedness measurement method used in this study considers various types of relationships in ontologies and derived relationships via an inference engine for computing relatedness. We hypothesized that rich variety of relationships and inferred facts in ontologies would improve the success of text coherence assessment. Our results demonstrate that the use of ontologies yields to coherence values that have a higher correlation with human ratings.

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Section: Experiment: Measuring Text Coherence Using An Ontology‐basedmentioning

confidence: 99%

Section: Experiment: Measuring Text Coherence Using An Ontology‐basedmentioning

confidence: 99%

Section: Experiment: Measuring Text Coherence Using An Ontology‐basedmentioning

confidence: 99%

See 1 more Smart Citation

Assessment of text coherence using an ontology‐based relatedness measurement method

Giray¹,

Ünalır

2019

Expert Systems

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“…For instance, the Semantic Web Search Engine (SWSE) (Hogan, et al, 2011) adapts the architecture of the common Web search engines for the case of structured RDF data (it offers crawling, data enhancing, indexing and a user interface for search, browsing and retrieval of RDF data). Swoogle (Ding, et al, 2004) is a crawler-based indexing and retrieval system for the Semantic Web that uses multiple crawlers to discover Semantic Web Documents (SWDs) through meta-search and link-following, analyzes SWDs and produces metadata, computes ranks of SWDs using a rational random surfing model, and indexes SWDs using an information retrieval system. Sindice (Oren, et al, 2008) is an indexing infrastructure with a Web front-end and a public API to locate Semantic Web data sources such as RDF files and SPARQL endpoints.…”

Section: Framework/systems For Quality Assessmentmentioning

confidence: 99%

Quantifying the Connectivity of a Semantic Warehouse and Understanding Its Evolution Over Time

Mountantonakis

Minadakis

Marketakis

et al. 2018

Information Retrieval and Management

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In many applications one has to fetch and assemble pieces of information coming from more than one source for building a semantic warehouse offering more advanced query capabilities. In this paper the authors describe the corresponding requirements and challenges, and they focus on the aspects of quality and value of the warehouse. For this reason they introduce various metrics (or measures) for quantifying its connectivity, and consequently its ability to answer complex queries. The authors demonstrate the behaviour of these metrics in the context of a real and operational semantic warehouse, as well as on synthetically produced warehouses. The proposed metrics allow someone to get an overview of the contribution (to the warehouse) of each source and to quantify the value of the entire warehouse. Consequently, these metrics can be used for advancing data/endpoint profiling and for this reason the authors use an extension of VoID (for making them publishable). Such descriptions can be exploited for dataset/endpoint selection in the context of federated search. In addition, the authors show how the metrics can be used for monitoring a semantic warehouse after each reconstruction reducing thereby the cost of quality checking, as well as for understanding its evolution over time.

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“…If Bouguer Anomaly maps are semantically annotated, for example, with the use of CI-Miner, and published in a place that can be indexed by a semantic-aware search engine such as IWSearch (Pinheiro da and Swoogle (Ding et al 2004), then the scientist may be able to locate the appropriate map.…”

Section: Search and Query Capabilitiesmentioning

confidence: 99%

CI-Miner: semantically enhancing scientific processes

et al. 2009

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The realization of an international cyberinfrastructure of shared resources to overcome time and space limitations is challenging scientists to rethink how to document their processes. Many known scientific process requirements that would normally be considered impossible to implement a few years ago are close to becoming a reality for scientists, such as large scale integration and data reuse, data sharing across distinct scientific domains, comprehensive support for explaining process results, and full search capability for scientific products across domains. This article introduces the CI-Miner approach that can be used to aggregate knowledge about scientific processes and their products through the use of semantic annotations. The article shows how this aggregated knowledge is used to benefit scientists during the development of their research activities. The discussion is grounded on lessons learned through the use of CI-Miner to semantically annotate scientific processes in the areas of geo-sciences,

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Swoogle

Cited by 533 publications

References 7 publications

Assessment of text coherence using an ontology‐based relatedness measurement method

Assessment of text coherence using an ontology‐based relatedness measurement method

Quantifying the Connectivity of a Semantic Warehouse and Understanding Its Evolution Over Time

CI-Miner: semantically enhancing scientific processes

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