• Conferenza GARR 2018

     

     

       GARR Conference is the annual meeting of users, operators and managers of the Italian national education and research network aimed at sharing experiences and comments on the use of the network as a tool for research, training and culture, in different contexts and disciplines.
   

     

     

Temi della conferenza    

Temi della conferenza    

The core themes of this editions are data, artificial intelligence and technology transfer both towards the enterprises and single persons. We will talk about open data and services, cybersecurity, industry 4.0 and its relations with research and innovation. We will discuss how education should be rethought in order to keep the pace with the continuous evolution of ICTs, also with the help of these very same technologies.   

Programme

Corsi di formazione   

Corsi di formazione   

On 1-2 October there will be several training opportunities for GARR user community. These courses span from classes dedicated to trainers (Moodle: how to manage a course e How to create and disseminate educational material online), to courses on Public Speaking, on cybersecurity (PenTest & Rooting) and on networking (Software Defined Network). For registrations to these training courses, go to the Learning GARR platform.    

Programme

4 ottobre 2018

Mattia Atzeni

Università di Cagliari
https://www.unica.it
Mattia Atzeni

 

Presentazione

Slide

Traduzione in codice di domande espresse in linguaggio naturale

Mattia Atzeni ha conseguito la Laurea Magistrale in Informatica presso l'Università degli Studi di Cagliari ad Aprile 2018. Attualmente, ha una borsa di ricerca presso la stessa università e i suoi principali interessi includono l'elaborazione del linguaggio naturale e il Machine Learning.

Mattia Atzeni received his Master's Degree in Computer Science at the University of Cagliari in April 2018. Currently, he has a research grant at the same university and his main interests include natural language processing and Machine Learning.

SESSIONE 6. INDUSTRIA 4.0 E IOT

Traduzione in codice di domande espresse in linguaggio naturale

In questo lavoro, descriviamo una struttura semantica per il recupero automatico e l'esecuzione del codice open source. Per affrontare questo compito, introduciamo CodeOntology, come approccio per applicare tecnologie semantiche note per rendere il codice sorgente un “cittadino di prima classe” del Web, dove può essere interconnesso con altre risorse, consentendo analisi interessanti che al giorno d'oggi sono impossibili. Successivamente, proponiamo un algoritmo che si basa su CodeOntology per interrogare il codice sorgente e recuperare un insieme di metodi e frammenti di codice che sono classificati e combinati per tradurre una specifica del linguaggio naturale in un codice sorgente Java.

A Semantic Framework for the Retrieval and Execution of Open Source Code

In this work, we describe a semantic framework for the automatic retrieval and execution of open source code. To address this task, we introduce CodeOntology, as an approach to apply well-known semantic technologies to make source code a first-class citizen of the Web, where it can be interlinked with other resources, enabling interesting analyses that are nowadays impossible. Next, we propose an algorithm which relies on CodeOntology for querying source code to retrieve a set of methods and code snippets that are ranked and combined to translate a natural language specification into a Java source code.

 

Sponsor

DELL EMC
Palo Alto Networks
INTEL
juniper networks
maticmind
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