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      <title-group>
        <article-title>A brief guided tour along the borders of Logic Programming with Description Logics</article-title>
      </title-group>
      <contrib-group>
        <contrib contrib-type="author">
          <string-name>Francesca A. Lisi</string-name>
          <email>francesca.lisi@uniba.it</email>
          <xref ref-type="aff" rid="aff0">0</xref>
          <xref ref-type="aff" rid="aff1">1</xref>
        </contrib>
        <aff id="aff0">
          <label>0</label>
          <institution>Dipartimento di Informatica, Universita degli Studi \A. Moro" di Bari Via E. Orabona 4</institution>
          ,
          <addr-line>70125 Bari</addr-line>
          ,
          <country country="IT">Italy</country>
        </aff>
        <aff id="aff1">
          <label>1</label>
          <institution>F. Baader</institution>
          ,
          <addr-line>D. Calvanese, D. McGuinness, D. Nardi, and P.F. Patel-Schneider, editors. The Description Logic Handbook: Theory</addr-line>
          ,
          <institution>Implementation and Applications. Cambridge University Press</institution>
          ,
          <addr-line>2003</addr-line>
        </aff>
      </contrib-group>
      <pub-date>
        <year>2015</year>
      </pub-date>
      <abstract>
        <p>Logic Programming (LP) (14) and the family of Description Logics (DLs) (1) are both based on fragments of First Order Logic (FOL). However, they are characterized by di erent semantic assumptions (16; 9). Yet, a partial overlap exists between LP and DLs which allows the extension and/or adaptation of known results in LP to DLs and viceversa (5; 17; 7; 8). Even more interestingly, a combination of the two is possible via several integration schemes that are aimed at designing very expressive FOL languages and ultimately overcoming the aforementioned semantic mismatch between LP and DLs (2; 10; 19; 15; 4; 3). Several works in Inductive Logic Programming (ILP) (born at the intersection between LP and concept learning (18)) testify the great potential of these hybrid knowledge representation formalisms also from the perspective of machine learning and inductive reasoning (20; 6; 11; 12; 13). This tutorial talk surveys the literature of the last 20 years concerning the combination of (I)LP and DLs with a particular emphasys on the integration issues. The aim is to show how many interesting things happen or could happen along the borders of LP with DLs. Francesco M. Donini, Maurizio Lenzerini, Daniele Nardi, and Andrea Schaerf. AL-log: Integrating Datalog and Description Logics. Journal of Intelligent Information Systems, 10(3):227{252, 1998. Thomas Eiter, Giovambattista Ianni, Thomas Lukasiewicz, and Roman Schindlauer. Wellfounded semantics for description logic programs in the semantic web. ACM Transactions on Computational Logic, 12(2):11, 2011. Thomas Eiter, Giovambattista Ianni, Thomas Lukasiewicz, Roman Schindlauer, and Hans Tompits. Combining answer set programming with description logics for the semantic web. Arti cial Intelligence, 172(12-13):1495{1539, 2008. Benjamin N. Grosof, Ian Horrocks, Raphael Volz, and Stefan Decker. Description logic programs: combining logic programs with description logic. In Proceedings of the 12th International World Wide Web Conference, pages 48{57. ACM, 2003. Jorg-Uwe Kietz. Learnability of description logic programs. In Stan Matwin and Claude Sammut, editors, Inductive Logic Programming, 12th International Conference, ILP</p>
      </abstract>
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