Seminari su Semantic Web Technologies
Dal 12.05.2014 al 13.05.2014
Lunedi 12, e Martedi 13 Maggio, la Dr. Zhengjie Fan, che ha conseguito recentemente a Grenoble (Francia) un PhD in Computer Science presso il Gruppo di Ricerca Exmo dell’INRIA (http://exmo.inrialpes.fr/), terrà un ciclo di due Seminari sulle problematiche delle Semantic Web Technologies.
Il primo seminario del 12 Maggio, della durata di 45 minuti più discussione, illustrerà principalmente la metodologia per il Data Sets Interlinking sviluppata dalla Dr. Fan nella sua Tesi di Dottorato, e si rivolge ai giovani dottorandi, e ai docenti e ricercatori, del Dipartimento.
Il secondo seminario del 13 Maggio, della durata di 90 minuti, affronta la problematica della semantica dei dati sul Web riguardo alle sue potenziali applicazioni alla Robotica, facendo particolare riferimento al progetto RoboEarth (a World Wide Web for robots) perseguito negli anni recenti presso alcune Università Europee (http://roboearth.org/) , al fine di rileggerne criticamente vantaggi e limiti.
Questo Seminario viene svolto nell’ambito delle attività integrative dell’Insegnamento di Robotica Autonoma, ma è aperto anche alla partecipazione dei giovani dottorandi, e dei docenti e ricercatori, del Dipartimento.
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Sede, Orario e Sommario dei Seminari:
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Lunedi 12 Maggio 2014, Sala Riunioni DEI/G, h. 17:00
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Dr. Zhengjie Fan
Title: Concise Pattern Learning for RDF Data Sets Interlinking
Abstract:
There are many data sets being published on the web with Semantic Web technology. The data sets contain analogous data which represent the same resources in the world. If these data sets are linked together by correctly building links, users can conveniently query data through a uniform interface, as if they are querying one data set. However, finding correct links is very challenging because there are many instances to compare. In this talk, an interlinking method is proposed to interlink the same instances across different data sets, based on both statistical learning and symbolic learning. The input is two data sets, class correspondences across the two data sets and a set of sample links that are assessed by users as either "positive" or "negative". The method builds a classifier that distinguishes correct links and incorrect links across two RDF data sets with the set of assessed sample links.
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Martedi 13 Maggio 2014, Sala Riunioni DEI/G, h. 16:30
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Dr. Zhengjie Fan
Title: Applying Semantic Web to Robotics
Abstract:
Semantic Web aims to express semantics of data on the web, so that users can share more information and let computers do more computations for them. Researchers have applied technologies of Semantic Web in the field of Robotics. They try to build a semantic web for robots in order to share action experiences and other data such as, map. The course is going to estimate the usefulness of Semantic Web for Robotics. First, basic knowledge of Semantic Web is introduced. They are the XML, RDF and OWL languages as well as Linked Open Data. Second, the RoboEarth project and KnowRob are introduced. Third, the potential research problems and challenges are discussed, if we apply Semantic Web into Robotics.
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Dr. Zhengjie Fan – Short Biography
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Zhengjie Fan is a fresh PhD graduate from University of Grenoble. During her PhD, under the supervision of Dr. Jérôme Euzenat and Prof. Francois Scharffe, she did research on "Interlinking RDF Data Sets" in the EXMO group of INRIA Grenoble, France. Before joining INRIA, she once worked for one year as a researcher in Delft University of Technology, the Netherlands, on the topics "Ontology Modeling of Emergency Response" and "Data Transformation for Spatial Data Sets". She got her Master degree in Computer Engineering from University of Science and Technology of China, Hefei, in 2008, under the supervision of Prof. Xiaoping Chen.
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