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      <title-group>
        <article-title>Semantic Web and Information Extraction SWAIE 2012</article-title>
      </title-group>
      <contrib-group>
        <aff id="aff0">
          <label>0</label>
          <institution>Edited by: Diana Maynard Marieke van Erp Brian Davis</institution>
        </aff>
        <aff id="aff1">
          <label>1</label>
          <institution>Workshop in conjunction with the 18th International Conference on Knowledge Engineering and Knowledge Management Galway City, Ireland</institution>
          ,
          <addr-line>9</addr-line>
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      </contrib-group>
      <pub-date>
        <year>2012</year>
      </pub-date>
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      <title>-</title>
      <p>There is a vast wealth of information available in textual format that the
Semantic Web cannot yet tap into: 80% of data on the Web and on internal corporate
intranets is unstructured, hence analysing and structuring the data - social
analytics and next generation analytics - is a large and growing endeavour. The goal
of the 1st workshop on Semantic Web and Information Extraction was to bring
researchers from the fields of Information Extraction and the Semantic Web
together to foster inter-domain collaboration. To make sense of the large amounts
of textual data now available, we need help from both the Information
Extraction and Semantic Web communities. The Information Extraction community
specialises in mining the nuggets of information from text: such techniques
could, however, be enhanced by annotated data or domain-specific resources.
The Semantic Web community has already taken great strides in making these
resources available through the Linked Open Data cloud, which are now ready
for uptake by the Information Extraction community. The workshop invited
contributions around three particular topics: 1) Semantic Web-driven
Information Extraction, 2) Information Extraction for the Semantic Web, and 3)
applications and architectures on the intersection of Semantic Web and Information
Extraction.</p>
      <p>SWAIE 2012 had a number of high-quality submissions. From these, the 6
best papers were chosen for the two paper sessions of the programme: 4 long
paper presentations and 2 short ones. Additionally, we held a lightning talks
session where attendees could present brief 3-minute talks about late-breaking
work or demos around the workshop themes, and a panel session involving some
general discussion about these themes. To initiate the workshop, a keynote talk
was provided by D.J. McCloskey, NLP Architect in IBM’s new Watson Solutions
division. The keynote presented the post-Watson role of Information Extraction
and its intersection with the Semantic Web.</p>
      <p>We would like to thank the many people who helped make SWAIE 2012
such a success: the Programme Committee, the paper contributors, the invited
speaker and panellists, and all the participants present at the workshop who
engaged in lively debate.</p>
      <p>Diana Maynard, University of Sheeld
Marieke van Erp, VU University Amsterdam
Brian Davis, DERI Galway
Programme Committee
• Georgeta Bordea, DERI Galway, Ireland
• Matje van de Camp, Tilburg University, The Netherlands
• Christian Chiarcos, Information Sciences Institute, USA
• Hamish Cunningham, University of Sheeld, UK
• Thierry DeClerck, DFKI, Germany
• Robert Engels, Western Norwegian Research Institute, Norway
• Phil Gooch, City University London, UK
• Seth Grimes, Alta Plana Corporation
• Siegfried Handschuh, DERI, Ireland
• Dirk Hovy, Information Sciences Institute, USA
• Laurette Pretorius, University of South Africa, South Africa
• Birgit Proell, Johannes Kepler University of Linz, Austria
• Giusseppe Rizzo, EURECOM, France
• Piek Vossen, VU University, The Netherlands
• Marie Wallace, IBM Dublin, Ireland
• Ren´e Witte, Concordia University, Montreal, Canada</p>
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    <ref-list>
      <ref id="ref1">
        <mixed-citation>
          <article-title>Unsupervised Improvement of Named Entity Extraction in Short Informal Context Using Disambiguation Clues Mena B</article-title>
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          <string-name>
            <surname>Maurice van Keulen . . . . . . . . . . 1</surname>
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          <article-title>LODIE: Linked Open Data for Web-scale Information Extraction Fabio Ciravegna, Anna Lisa Gentile</article-title>
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          <article-title>Ontologies as a Source for the Automatic Generation of Grammars for Information Extraction Systems Thierry Declerck</article-title>
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          <article-title>Identifying Consumers' Arguments in Text Jodi Schneider</article-title>
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            <surname>Identifying and Extracting Quantitative Data in Annotated Text Don J. M. Willems</surname>
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            <surname>Scenario-Driven Selection</surname>
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          and Jos´
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