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          <h3>NMR Online Seminar</h3>
          <p><br>
            <font face="monospace"><font size="4">-- Summary:
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                <br>
                What?    Next talk in the NMR online talk series by
                Vanina Martinez<br>
                When?    Wednesday, 22. October 2025, 16:00 CEST (UCT+2)<br>
                Where?   Online (Zoom):
<a class="moz-txt-link-freetext" href="https://uct-za.zoom.us/j/92600685092?pwd=ErqWWWKrljbjxLi0CNsgEZr4WR7ZHN.1">https://uct-za.zoom.us/j/92600685092?pwd=ErqWWWKrljbjxLi0CNsgEZr4WR7ZHN.1</a><br>
                <br>
                <a class="moz-txt-link-freetext"
                  href="https://nmrseminar.krportal.org/">https://nmrseminar.krportal.org/</a><br>
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            We are happy to announce that the NMR online talk series
            restarts after the summer break with a talk given by<br>
               <b>Vanina Martinez</b> (<span><span>IIIA-CSIC</span></span>,
            Spain)<br>
               on <b>Wednesday, 22. October 2025</b>, 16:00 CEST:</p>
          <p><span><span style="font-weight: bold;">Making Sense of
                Messy Graphs: Addressing Uncertainty in Data-Graphs<br>
              </span></span><font size="2">Graph databases are becoming
              widely successful as data models that allow for effective
              representation and processing of complex relationships
              among various types of data. Data graphs are a particular
              type of graph database whose representation enables both
              data to values in the paths and in the nodes to be treated
              as first-class citizens by the query language. As with any
              other type of data repository, data graphs may suffer from
              errors and discrepancies with respect to the real-world
              data they intend to represent.<br>
              In this talk, I will present part of the work we have been
              doing exploring the notion of probabilistic unclean
              data-graphs, to capture the idea that the observed
              (unclean) data-graph is actually the noisy version of a
              clean one that correctly models the world, but that we
              know only partially. As the factors that lead to such a
              state of affairs may be many, e.g., all different types of
              clerical errors or unintended transformations of the data,
              and depend heavily on the application domain, we assume an
              epistemic probabilistic model that describes the
              distribution over all possible ways in which the clean
              (uncertain) data-graph could have been polluted. Based on
              this model, we define two computational problems: data
              cleaning and probabilistic query answering, and study
              their computational complexity and limitations. </font><br>
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          <p>The talk will be given via Zoom.</p>
          <p>The plan of this series to have a talk roughly once per
            month. If you are interested in learning the next speakers,
            please visit the website at<br>
               <a class="moz-txt-link-freetext"
              href="https://nmrseminar.krportal.org/">https://nmrseminar.krportal.org/</a></p>
          <p>We are still looking for speakers for future talks. If
            there is something you would like to present in this seminar
            series, please do not hesitate to contact us.</p>
          Kind regards,<br>
          Jonas and Giovanni<br>
          <br>
          <p></p>
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