Matches in ScholarlyData for { ?s ?p ?o. }
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- item-1 hasContent dezhao-song.
- paper-08 type InProceedings.
- paper-08 label "Distributed Reasoning on Semantic Data Streams".
- paper-08 sameAs paper-08.
- paper-08 abstract "Data streams are being continually generated in diverse application domains such as traffic monitoring, smart buildings, and so on. Stream Reasoning is the area that aims to combine reasoning techniques with data streams. In this paper, we present our approach to enable rule-based reasoning on semantic data streams using data flow networks in a distributed manner.".
- paper-08 hasAuthorList authorList.
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- paper-08 title "Distributed Reasoning on Semantic Data Streams".
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- item-1 hasContent rehab-albeladi.
- paper-09 type InProceedings.
- paper-09 label "Reusing XML Schemas' Information as a Foundation for Designing Domain Ontologies".
- paper-09 sameAs paper-09.
- paper-09 abstract "Designing domain ontologies from scratch is a time-consuming endeavor requiring a lot of close collaboration with domain experts. However, domain descriptions such as XML Schemas are often available in early stages of the ontology development process. For my dissertation, I propose a method to convert XML Schemas to OWL ontologies in an automatic way. The approach addresses the transformation of any XML Schema documents by using the XML Schema metamodel, which is completely represented by the XML Schema Metamodel Ontology. Automatically, all Schema declarations and definitions are converted to class axioms, which are intended to be enriched with additional domain-specific semantic information in form of domain ontologies.".
- paper-09 hasAuthorList authorList.
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- paper-09 title "Reusing XML Schemas' Information as a Foundation for Designing Domain Ontologies".
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- item-1 hasContent thomas-bosch.
- paper-10 type InProceedings.
- paper-10 label "A Multi-Domain Framework for Community Building Based on Data Tagging".
- paper-10 sameAs paper-10.
- paper-10 abstract "In this paper, we present a doctoral thesis which introduces a new approach of time series enrichment with semantics. The paper shows the problem of assigning time series data to the right party of interest and why this problem could not be solved so far. We demonstrate a new way of processing semantic time series and the consequential ability of addressing users. The combination of time series processing and Semantic Web technologies leads us to a new powerful method of data processing and data generation, which offers completely new opportunities to the expert user.".
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- paper-10 title "A Multi-Domain Framework for Community Building Based on Data Tagging".
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- item-1 type ListItem.
- item-1 hasContent bojan-bozic.
- paper-11 type InProceedings.
- paper-11 label "Towards a theoretical foundation for the harmonization of linked data".
- paper-11 sameAs paper-11.
- paper-11 abstract "In real world cases, building reliable problem centric views over Linked Data is a challenging task. An ideal method should include a formal representation of the requirements of the needed dataset and a controlled process moving from the original sources to the outcome. We believe that a goal oriented approach, similar to the AI planning problem, could be successful in controlling the process of linked data fusion, as well as to formalize the relations between requirements, process and result.".
- paper-11 hasAuthorList authorList.
- paper-11 isPartOf proceedings-1.
- paper-11 title "Towards a theoretical foundation for the harmonization of linked data".
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- item-1 hasContent enrico-daga.
- paper-12 type InProceedings.
- paper-12 label "Knowledge Pattern Extraction and their usage in Exploratory Search".
- paper-12 sameAs paper-12.
- paper-12 abstract "Knowledge interaction in Web context is a challenging problem. For instance, it requires to deal with complex structures able to filter knowledge by drawing a meaningful context boundary around data. We assume that these complex structures can be formalized as Knowledge Patterns (KPs), aka frames. This Ph.D. work is aimed at developing methods for extracting KPs from the Web and at applying KPs to exploratory search tasks. We want to extract KPs by analyzing the structure of Web links from rich resources, such as Wikipedia.".
- paper-12 hasAuthorList authorList.
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- paper-12 title "Knowledge Pattern Extraction and their usage in Exploratory Search".
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- item-1 hasContent andrea-giovanni-nuzzolese.
- paper-13 type InProceedings.
- paper-13 label "SPARQL Update for Complex Event Processing".
- paper-13 sameAs paper-13.
- paper-13 abstract "Complex event processing is currently done primarily with proprietary definition languages. Future smart environments will require collaboration of multi-platform sensors operated by multiple parties. The goal of my research is to verify the applicability of standard-compliant SPARQL for complex event processing tasks. If successful, semantic web standards RDF, SPARQL and OWL with their established base of tools have many other benefits for event processing including support for interconnecting disjoint vocabularies, enriching event information with linked open data and reasoning over semantically annotated content. A software platform capable of continuous incremental evaluation of multiple parallel SPARQL queries is a key enabler of the approach.".
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- paper-13 title "SPARQL Update for Complex Event Processing".
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- item-1 type ListItem.
- item-1 hasContent mikko-rinne.
- paper-14 type InProceedings.
- paper-14 label "Online Unsupervised Coreference Resolution for Semi-Structured Heterogeneous Data".
- paper-14 sameAs paper-14.
- paper-14 abstract "A pair of RDF instances are said to corefer when they are intended to denote the same thing in the world, for example, when two nodes of type foaf:Person describe the same individual. This problem is central to integrating and inter-linking semi-structured datasets. We are developing an online, unsupervised coreference resolution framework for heterogeneous, semi-structured data. The online aspect requires us to process new instances as they appear and not as a batch. The instances are heterogeneous in that they may contain terms from different ontologies whose alignments are not known in advance. Our framework encompasses a two-phased clustering algorithm that is both flexible and distributable, a probabilistic multidimensional attribute model that will support robust schema mappings, and a consolidation algorithm that will be used to perform instance consolidation in order to improve accuracy rates over time by addressing data sparseness.".
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- paper-14 title "Online Unsupervised Coreference Resolution for Semi-Structured Heterogeneous Data".
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- item-1 hasContent jennifer-sleeman.
- paper-15 type InProceedings.
- paper-15 label "Composition of Linked Data-based RESTful Services".
- paper-15 sameAs paper-15.
- paper-15 abstract "We address the problem of developing a scalable composition framework for Linked Data-based services, which retains the advantages of the loose coupling fostered by REST.".