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- paper-15 label "Linked Data Fusion in ODCleanStore".
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- paper-15 abstract "As part of LOD2 project and OpenData.cz initiative, we are developing an ODCleanStore framework enabling management of Linked Data. In this paper, we focus on the query-time data fusion in ODCleanStore, which provides data consumers with integrated views on Linked Data; the fused data (1) has solved conflicts according to the preferred conflict resolution policies and (2) is accompanied with provenance and quality scores, so that the consumers can judge the usefulness and trustworthiness of the data for their task at hand.".
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- paper-15 title "Linked Data Fusion in ODCleanStore".
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- paper-16 label "Making Sense of Research with Rexplore".
- paper-16 sameAs paper-16.
- paper-16 abstract "While there are many tools and services which support the exploration of research data, by and large these tend to provide a limited set of functionalities, which cover primarily ranking measures and mechanisms for relating authors, typically on the basis of simple co-authorship relations. To try and improve over the current state of affairs, we are developing a novel tool for exploring research data, which is called Rexplore. Rexplore builds on an intelligent algorithm for automatically identifying hierarchical and equivalence relations between research areas, to provide a variety of functionalities and visualizations to help users to make sense of a research area. These include visualizations to detect trends in research; ways to cluster authors according to several dynamic similarity measures; and fine-grained mechanisms for ranking authors, taking into account parameters such as ranking criterion, career stage, calendar years, publication venues, etc.".
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- paper-16 title "Making Sense of Research with Rexplore".
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- paper-17 label "MeDetect: Domain Entity Annotation in Biomedical References Using Linked Open Data".
- paper-17 sameAs paper-17.
- paper-17 abstract "Recently, with the ever-growing of textual medicine records, annotating domain entities has been regarded as an important task in the biomedical field. On the other hand, the process of interlinking open data sources is actively pursued within the Linking Open Data (LOD) project. The number of entities and the number of properties describing semantic relationships between entities within the linked data cloud are very large. In this paper, we propose a knowledge-incentive approach based on LOD for entity annotation in the biomedical field. With this approach, we implement MeDetect, a prototype system to solve the problems mentioned above. The experimental results verify the effectiveness and efficiency of our approach.".
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- paper-17 title "MeDetect: Domain Entity Annotation in Biomedical References Using Linked Open Data".
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- paper-18 type InProceedings.
- paper-18 label "Mining Patterns from Clinical Trial Annotated Datasets by Exploiting the NCI Thesaurus".
- paper-18 sameAs paper-18.
- paper-18 abstract "Annotations of clinical trials with controlled vocabularies of drugs and diseases, encode scientific knowledge that can be mined to discover relationships between scientific concepts. We present PAnG (Patterns in Annotation Graphs), a tool that relies on dense subgraphs, graph summarization and taxonomic distance metrics, computed using the NCI Thesaurus, to identify patterns.".
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- paper-18 title "Mining Patterns from Clinical Trial Annotated Datasets by Exploiting the NCI Thesaurus".
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