<div dir="ltr"><div class="gmail_quote"><div dir="ltr"><span style="font-family:Georgia;font-size:13px">------------------------------</span><span style="font-family:Georgia;font-size:13px"><wbr>----------------</span><br style="line-height:1.22em;font-family:Georgia;font-size:13px"><span style="font-family:Georgia;font-size:13px">Apologies for cross-posting</span><br style="line-height:1.22em;font-family:Georgia;font-size:13px"><span style="font-family:Georgia;font-size:13px">------------------------------</span><span style="font-family:Georgia;font-size:13px"><wbr>----------------</span><br style="line-height:1.22em;font-family:Georgia;font-size:13px"><br style="line-height:1.22em;font-family:Georgia;font-size:13px"><span style="font-family:Georgia;font-size:13px">******************************</span><span style="font-family:Georgia;font-size:13px"><wbr>******************************</span><span style="font-family:Georgia;font-size:13px"><wbr>******************************</span><span style="font-family:Georgia;font-size:13px"><wbr>*</span><br style="line-height:1.22em;font-family:Georgia;font-size:13px"><span style="font-family:Georgia;font-size:13px">GenSW2017: 1st International Workshop on "Generalizing knowledge: from Machine Learning and </span><br style="line-height:1.22em;font-family:Georgia;font-size:13px"><span style="font-family:Georgia;font-size:13px">Knowledge Representation to the Semantic Web"</span><br style="line-height:1.22em;font-family:Georgia;font-size:13px"><br style="line-height:1.22em;font-family:Georgia;font-size:13px"><span style="font-family:Georgia;font-size:13px">Website: </span><a href="https://sites.google.com/site/gensw2017/" style="line-height:1.22em;font-family:Verdana;font-size:13px" target="_blank">https://sites.google.<wbr>com/site/gensw2017/</a><br style="line-height:1.22em;font-family:Georgia;font-size:13px"><br style="line-height:1.22em;font-family:Georgia;font-size:13px"><span style="font-family:Georgia;font-size:13px">In conjunction with with "The 16th International Conference of the Italian Association for </span><br style="line-height:1.22em;font-family:Georgia;font-size:13px"><span style="font-family:Georgia;font-size:13px">Artificial Intelligence" (AI*IA 2017), Bari, Italy, November 14 - 17 2017.</span><br style="line-height:1.22em;font-family:Georgia;font-size:13px"><span style="font-family:Georgia;font-size:13px">******************************</span><span style="font-family:Georgia;font-size:13px"><wbr>******************************</span><span style="font-family:Georgia;font-size:13px"><wbr>******************************</span><span style="font-family:Georgia;font-size:13px"><wbr>*</span><br style="line-height:1.22em;font-family:Georgia;font-size:13px"><br style="line-height:1.22em;font-family:Georgia;font-size:13px"><span style="font-family:Georgia;font-size:13px">IMPORTANT DATES</span><br style="line-height:1.22em;font-family:Georgia;font-size:13px"><span style="font-family:Georgia;font-size:13px">-----------------------</span><br style="line-height:1.22em;font-family:Georgia;font-size:13px"><span style="font-family:Georgia;font-size:13px">Abstract submission: 13 July 2017</span><br style="line-height:1.22em;font-family:Georgia;font-size:13px"><span style="font-family:Georgia;font-size:13px">Paper submission: 18 July 2017</span><br style="line-height:1.22em;font-family:Georgia;font-size:13px"><span style="font-family:Georgia;font-size:13px">Notification to authors: 8 September 2017</span><br style="line-height:1.22em;font-family:Georgia;font-size:13px"><span style="font-family:Georgia;font-size:13px">Camera-ready copies: 29 September 2017</span><br style="line-height:1.22em;font-family:Georgia;font-size:13px"><br style="line-height:1.22em;font-family:Georgia;font-size:13px"><span style="font-family:Georgia;font-size:13px">FOCUS</span><br style="line-height:1.22em;font-family:Georgia;font-size:13px"><span style="font-family:Georgia;font-size:13px">-----------------------</span><br style="line-height:1.22em;font-family:Georgia;font-size:13px"><span style="font-family:Georgia;font-size:13px">Generalizing descriptions is a problem traditionally investigated in at least two different fields </span><br style="line-height:1.22em;font-family:Georgia;font-size:13px"><span style="font-family:Georgia;font-size:13px">of Artificial Intelligence: Machine Learning (ML) and Knowledge Representation (KR). Both research </span><br style="line-height:1.22em;font-family:Georgia;font-size:13px"><span style="font-family:Georgia;font-size:13px">fields have played an important role in the development of the Semantic Web (SW).</span><br style="line-height:1.22em;font-family:Georgia;font-size:13px"><br style="line-height:1.22em;font-family:Georgia;font-size:13px"><span style="font-family:Georgia;font-size:13px">KR provided the theoretical basis for formalizing shared knowledge bases, a.k.a. ontologies, and </span><br style="line-height:1.22em;font-family:Georgia;font-size:13px"><span style="font-family:Georgia;font-size:13px">for deductively reasoning over them. ML methods have been used for enriching ontologies, both at </span><br style="line-height:1.22em;font-family:Georgia;font-size:13px"><span style="font-family:Georgia;font-size:13px">schema and instance level, by exploiting inductive reasoning, while still benefiting from deductive </span><br style="line-height:1.22em;font-family:Georgia;font-size:13px"><span style="font-family:Georgia;font-size:13px">reasoning, when possible.</span><br style="line-height:1.22em;font-family:Georgia;font-size:13px"><br style="line-height:1.22em;font-family:Georgia;font-size:13px"><span style="font-family:Georgia;font-size:13px">In the Web of Data, the availability of generalization mechanisms could be crucial for performing </span><br style="line-height:1.22em;font-family:Georgia;font-size:13px"><span style="font-family:Georgia;font-size:13px">several knowledge management tasks, such as data summarization, data indexing, cluster discovery and </span><br style="line-height:1.22em;font-family:Georgia;font-size:13px"><span style="font-family:Georgia;font-size:13px">many others. However, performing generalization in such a context cannot be done by just revisiting </span><br style="line-height:1.22em;font-family:Georgia;font-size:13px"><span style="font-family:Georgia;font-size:13px">traditional generalization services, because some issues and peculiarities need to be carefully </span><br style="line-height:1.22em;font-family:Georgia;font-size:13px"><span style="font-family:Georgia;font-size:13px">taken into account. One of these peculiarities is the data size, which requires new scalable </span><br style="line-height:1.22em;font-family:Georgia;font-size:13px"><span style="font-family:Georgia;font-size:13px">techniques. The second one is the data quality, which is affected by the endemic redundancy, noise, </span><br style="line-height:1.22em;font-family:Georgia;font-size:13px"><span style="font-family:Georgia;font-size:13px">frequent irrelevance and possible inconsistency of the available information. A third one is data </span><br style="line-height:1.22em;font-family:Georgia;font-size:13px"><span style="font-family:Georgia;font-size:13px">interdependency stemming from RDFS statements.</span><br style="line-height:1.22em;font-family:Georgia;font-size:13px"><br style="line-height:1.22em;font-family:Georgia;font-size:13px"><span style="font-family:Georgia;font-size:13px">Despite some preliminary research efforts, very few solutions and methods can be found at the state </span><br style="line-height:1.22em;font-family:Georgia;font-size:13px"><span style="font-family:Georgia;font-size:13px">of the art for coping with this urgent problem. The maturity of solutions coming from the ML and KR </span><br style="line-height:1.22em;font-family:Georgia;font-size:13px"><span style="font-family:Georgia;font-size:13px">fields may certainly provide a reasonable starting point. However, methods mixing or stacking </span><br style="line-height:1.22em;font-family:Georgia;font-size:13px"><span style="font-family:Georgia;font-size:13px">solutions coming from both fields may result more promising to address all raised issues. Therefore, </span><br style="line-height:1.22em;font-family:Georgia;font-size:13px"><span style="font-family:Georgia;font-size:13px">the main goal of the workshop is to foster solutions cross-fertilizing both ML and KR fields, </span><br style="line-height:1.22em;font-family:Georgia;font-size:13px"><span style="font-family:Georgia;font-size:13px">focusing on generalizing SW knowledge descriptions and, possibly taking into account scalability </span><br style="line-height:1.22em;font-family:Georgia;font-size:13px"><span style="font-family:Georgia;font-size:13px">issues. Solutions of interest should cope with descriptions formalized, primarily, in RDF/RDFS, but </span><br style="line-height:1.22em;font-family:Georgia;font-size:13px"><span style="font-family:Georgia;font-size:13px">also in more expressive representation languages, like Description Logics/OWL.</span><br style="line-height:1.22em;font-family:Georgia;font-size:13px"><br style="line-height:1.22em;font-family:Georgia;font-size:13px"><span style="font-family:Georgia;font-size:13px">The workshop aims at gathering solutions for the generalization of knowledge descriptions </span><br style="line-height:1.22em;font-family:Georgia;font-size:13px"><span style="font-family:Georgia;font-size:13px">formalized in standard representation languages for the Semantic Web (primarily, but not only, </span><br style="line-height:1.22em;font-family:Georgia;font-size:13px"><span style="font-family:Georgia;font-size:13px">RDF/RDFS). Solutions of interest should focus (primarily, but not only) on methods mixing and/or </span><br style="line-height:1.22em;font-family:Georgia;font-size:13px"><span style="font-family:Georgia;font-size:13px">stacking solutions coming from Machine Learning and Knowledge Representation fields and applicable </span><br style="line-height:1.22em;font-family:Georgia;font-size:13px"><span style="font-family:Georgia;font-size:13px">to standard Semantic Web representation languages. The developments of scalable solutions for this </span><br style="line-height:1.22em;font-family:Georgia;font-size:13px"><span style="font-family:Georgia;font-size:13px">purpose will be particularly appreciated.</span><br style="line-height:1.22em;font-family:Georgia;font-size:13px"><br style="line-height:1.22em;font-family:Georgia;font-size:13px"><span style="font-family:Georgia;font-size:13px">TOPICS</span><br style="line-height:1.22em;font-family:Georgia;font-size:13px"><span style="font-family:Georgia;font-size:13px">------------------------------</span><span style="font-family:Georgia;font-size:13px"><wbr>--------------------</span><br style="line-height:1.22em;font-family:Georgia;font-size:13px"><span style="font-family:Georgia;font-size:13px">Topics of interest include, but are not limited to:</span><br style="line-height:1.22em;font-family:Georgia;font-size:13px"><br style="line-height:1.22em;font-family:Georgia;font-size:13px"><span style="font-family:Georgia;font-size:13px">· KR and/or ML methods (possibly in combination) for generalizing in the Semantic Web</span><br style="line-height:1.22em;font-family:Georgia;font-size:13px"><span style="font-family:Georgia;font-size:13px">· Semi-supervised, unbalanced, inductive learning for generalizing in the Semantic Web</span><br style="line-height:1.22em;font-family:Georgia;font-size:13px"><span style="font-family:Georgia;font-size:13px">· Reasoning services for generalization in the Semantic Web</span><br style="line-height:1.22em;font-family:Georgia;font-size:13px"><span style="font-family:Georgia;font-size:13px">- Generalization methods for finding commonalities and differences in the Semantic Web</span><br style="line-height:1.22em;font-family:Georgia;font-size:13px"><span style="font-family:Georgia;font-size:13px">- Generalization methods for enrichment Semantic Web knowledge bases</span><br style="line-height:1.22em;font-family:Georgia;font-size:13px"><span style="font-family:Georgia;font-size:13px">- Generalization methods for indexing in the Linked Data Cloud</span><br style="line-height:1.22em;font-family:Georgia;font-size:13px"><span style="font-family:Georgia;font-size:13px">· Evaluation and benchmarking of generalization approaches in the Semantic Web</span><br style="line-height:1.22em;font-family:Georgia;font-size:13px"><span style="font-family:Georgia;font-size:13px">· Scalable algorithms for generalizing the Web of Data</span><br style="line-height:1.22em;font-family:Georgia;font-size:13px"><span style="font-family:Georgia;font-size:13px">· Generalization in presence of uncertain/inconsistent/noisy knowledge</span><br style="line-height:1.22em;font-family:Georgia;font-size:13px"><br style="line-height:1.22em;font-family:Georgia;font-size:13px"><span style="font-family:Georgia;font-size:13px">Papers should be written in English, formatted according to the Springer LNCS style, and not exceed </span><br style="line-height:1.22em;font-family:Georgia;font-size:13px"><span style="font-family:Georgia;font-size:13px">12 pages (full papers) or 4 pages (position papers) plus bibliography.</span><br style="line-height:1.22em;font-family:Georgia;font-size:13px"><span style="font-family:Georgia;font-size:13px">Papers must be submitted via easychair: </span><a href="https://easychair.org/conferences/?conf=gensw2017" style="line-height:1.22em;font-family:Verdana;font-size:13px" target="_blank">https://easychair.<wbr>org/conferences/?conf=<wbr>gensw2017</a><span style="font-family:Georgia;font-size:13px">.</span><br style="line-height:1.22em;font-family:Georgia;font-size:13px"><br style="line-height:1.22em;font-family:Georgia;font-size:13px"><span style="font-family:Georgia;font-size:13px">All accepted papers will be scheduled for oral presentations and will be published in CEUR Workshop </span><br style="line-height:1.22em;font-family:Georgia;font-size:13px"><span style="font-family:Georgia;font-size:13px">Proceedings AI*IA Series.</span><br style="line-height:1.22em;font-family:Georgia;font-size:13px"><br style="line-height:1.22em;font-family:Georgia;font-size:13px"><span style="font-family:Georgia;font-size:13px">******************************</span><span style="font-family:Georgia;font-size:13px"><wbr>******************************</span><span style="font-family:Georgia;font-size:13px"><wbr>******************************</span><span style="font-family:Georgia;font-size:13px"><wbr>*********</span><br style="line-height:1.22em;font-family:Georgia;font-size:13px"><span style="font-family:Georgia;font-size:13px">Authors of selected papers accepted to the workshop will be invited to submit an extended version </span><br style="line-height:1.22em;font-family:Georgia;font-size:13px"><span style="font-family:Georgia;font-size:13px">for publication on a SPECIAL ISSUE for the journal “Semantic Web – Interoperability, Usability, </span><br style="line-height:1.22em;font-family:Georgia;font-size:13px"><span style="font-family:Georgia;font-size:13px">Applicability" (</span><a href="http://www.semantic-web-journal.net/" style="line-height:1.22em;font-family:Verdana;font-size:13px" target="_blank">http://www.semantic-web-journ<wbr>al.net/</a><span style="font-family:Georgia;font-size:13px">). Papers selected for the special issue have to </span><br style="line-height:1.22em;font-family:Georgia;font-size:13px"><span style="font-family:Georgia;font-size:13px">go through a full review process before acceptance.</span><br style="line-height:1.22em;font-family:Georgia;font-size:13px"><span style="font-family:Georgia;font-size:13px">******************************</span><span style="font-family:Georgia;font-size:13px"><wbr>******************************</span><span style="font-family:Georgia;font-size:13px"><wbr>******************************</span><span style="font-family:Georgia;font-size:13px"><wbr>*********</span><br style="line-height:1.22em;font-family:Georgia;font-size:13px"><br style="line-height:1.22em;font-family:Georgia;font-size:13px"><span style="font-family:Georgia;font-size:13px">ORGANIZING COMMITTEE</span><br style="line-height:1.22em;font-family:Georgia;font-size:13px"><span style="font-family:Georgia;font-size:13px">-----------------------------</span><br style="line-height:1.22em;font-family:Georgia;font-size:13px"><span style="font-family:Georgia;font-size:13px">Simona Colucci, Politecnico di Bari</span><br style="line-height:1.22em;font-family:Georgia;font-size:13px"><span style="font-family:Georgia;font-size:13px">Claudia d'Amato, Università degli Studi di Bari</span><br style="line-height:1.22em;font-family:Georgia;font-size:13px"><span style="font-family:Georgia;font-size:13px">Francesco M. Donini, Università della Tuscia, Viterbo</span><div><font face="Georgia"><br></font></div><div><font face="Georgia"><br></font></div><div><font face="Georgia"><br></font></div><div><font face="Georgia"><br></font></div><div><font face="Georgia"><br clear="all"></font><div><div class="m_-6874075473531405151gmail_signature"><div dir="ltr"><div><div dir="ltr"><div><div dir="ltr"><div><div dir="ltr"><span style="font-family:Helvetica,Arial,Verdana,serif;font-size:12.8px">Simona Colucci, Ph.D.</span><div><font face="Helvetica, Arial, Verdana, serif">Assistant Professor<br></font><div><font face="Helvetica, Arial, Verdana, serif">Politecnico di Bari<br></font><div>Department of Electrical and Information Engineering<br style="font-family:Helvetica,Arial,Verdana,serif;font-size:12.8px"><a href="http://sisinflab.poliba.it/" style="color:rgb(0,68,119);text-decoration:none;border:0px solid;font-family:Helvetica,Arial,Verdana,serif;font-size:12.8px" target="_blank">Information Systems</a><span style="font-family:Helvetica,Arial,Verdana,serif;font-size:12.8px"> Research Group</span><br style="font-family:Helvetica,Arial,Verdana,serif;font-size:12.8px"><span style="font-family:Helvetica,Arial,Verdana,serif;font-size:12.8px"><b>Address</b>: via E. Orabona, 4 - 70125 Bari</span><br style="font-family:Helvetica,Arial,Verdana,serif;font-size:12.8px"><span style="font-family:Helvetica,Arial,Verdana,serif;font-size:12.8px"><b>Tel:</b>  <a href="tel:+39%20080%20596%203222" value="+390805963222" target="_blank">+ 39 080 596 3222</a></span><br style="font-family:Helvetica,Arial,Verdana,serif;font-size:12.8px"><strong style="font-family:Helvetica,Arial,Verdana,serif;font-size:12.8px">Fax</strong><span style="font-family:Helvetica,Arial,Verdana,serif;font-size:12.8px">: <a href="tel:+39%20080%20596%203410" value="+390805963410" target="_blank">+ 39 080 596 3410</a></span><br></div></div></div></div></div></div></div></div></div></div></div></div>
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