DeliverablesFrom Kolflow Project
Published DeliverablesTo access deliverables just click on the deliverable number
Expended list of delivrablesD11Deliverable descriptionCode : D1.1 Task / Sub-task : Task1 Deadline : month 0 Description : kick off meeting Concerns : Kick-off meeting Status : yes
D12Deliverable descriptionCode : D1.2 Task / Sub-task : Task1 Deadline : month 3 Description : creation and continuous updates Concerns : Kolflow Status : true
D13Deliverable descriptionCode : D1.3 Task / Sub-task : Task1 Deadline : month 12 Description : Yearly workshop 1 Concerns : Yearly workshop 1 Status : yes
D21Deliverable descriptionCode : D2.1 Task / Sub-task : Task21 Deadline : month 6 Description : Building a corpus for experimenting continuous knowledge extraction. Concerns : Status : yes
sparql endpoint are now available from the main page of wikitaaable.loria.fr.
Deliverable descriptionCode : D2.2 Task / Sub-task : Task22 Deadline : month 12 Description : Integrating a knowledge extraction system from texts in a semantic wiki. methodology, modules, and experiments. Concerns : Status : yes
Deliverable descriptionCode : D3.1 Task / Sub-task : Task3 Deadline : month 12 Description : algorithms and architecture of the interactive semantic inconsistency managing system Concerns : Status : yes
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Deliverable descriptionCode : D4.1 Task / Sub-task : Task4 Deadline : month 6 Description : State of the art on the different topics addressed in this task Concerns : Status : yes
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Deliverable descriptionCode : D4.2 Task / Sub-task : Task4 Deadline : month 10 Description : Algorithm to explain basic query mechanisms Concerns : Status : yes
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Deliverable descriptionCode : D5.1 Task / Sub-task : Task5 Deadline : month 6 Description : State of the art on the three topics studied (Distributed Semantic Wikis, distributed querying distributed alter-ego assistant), Concerns : Status : yes
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Deliverable descriptionCode : D5.2 Task / Sub-task : Task5 Deadline : month 12 Description : Many semantic web applications integrate data from distributed triple stores and to be efficient, they need to know what kind of content each triple store holds in order to assess if it can contribute to its queries. We present an algorithm to build indexes summarizing the content of triple stores. We extended Depth-First Search coding to provide a canonical representation of RDF graphs and we introduce a new join operator between two graph codes to optimize the generation of an index. We provide an incremental update algorithm and conclude with tests on real datasets. Concerns : Kolflow Status : yes
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Deliverable descriptionCode : D6.1 Task / Sub-task : Task6 Deadline : month 6 Description : Man-machine collaboration scenarios Concerns : Status : yes
This deliverable has been joined with Deliverables D62. In addition, some assistance scenarios are described in this Media:assistance_document.pdf.D62Deliverable descriptionCode : D6.2 Task / Sub-task : Task6 Deadline : month 12 Description : Man-machine collaboration scenarios progress report Concerns : Status : yes
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