Data Moove Research & Development | DATA-MOOVE

Data Moove Research & Development

A research and development of Data-Moove S.A.S. is focused on a single objective: innovation in the sharing, management and organization of mass data via new technologies.

EURECOM logoIn order to reinforce its status as an actor in this field, Data-Moove has brought EURECOM into its capital.

This close partnership between our company and this Sophipolitain research center, specializing in the digital sciences, enables us to accelerate the transfer of knowledge accumulated for nearly 5 years with key players such as SAP, ORANGE, BMW or SYMANTEC.

Thus, this win-win partnership with Data-Moove makes it possible to test in real conditions the performance of technologies developed in the laboratory in order to move from basic research to applied research.

 

To meet the trend of sustainable development “Smart City“, Data Moove offers technological innovations:

  • Data collection and harvestingbigdata
  • Data identification
  • Data de-duplication,
  • Data model standardization,
  • Data classification,
  • Data edition,
  • Data publishing,

The data is available on various mediums: PCs, smartphones, tablets, Interactive boards, widgets, social networks, …

atelier-smart-mobility_0The Data Moove R&D strategy aims to respond to the major issues at the heart of the Smart City trend:

  • Access to information and connected cities;
  • Optimization of information processing;
  • Predictive statistics;
  • IoT;
  • Mobility.

 

 

Publications : 

3cixty (City Moove)

2017:
Raphaël Troncy, Giuseppe Rizzo, Anthony Jameson, Oscar Corcho, Julien Plu, Enrico Palumbo, Juan Carlos Ballesteros Hermida, Adrian Spirescu, Kai-Dominik Kuhn, Catalin Barbu, Matteo Rossi, Irene Celino, Rachit Agarwal, Christian Scanu, Massimo Valla and Timber Haaker. 3cixty: Building comprehensive knowledge bases for city exploration. In Journal of Web Semantics (JWS), 2017
https://doi.org/10.1016/j.websem.2017.07.002

2016:
Giuseppe Rizzo, Rosa Meo, Ruggero G. Pensa, Giacomo Falcone and Raphaël Troncy. Shaping City Neighborhoods Leveraging Crowd Sensors. In Information Systems, Special Issue on Mining Urban Data, 2016
http://dx.doi.org/10.1016/j.is.2016.06.009

Houda Khrouf and Raphaël Troncy. EventMedia: a LOD Dataset of Events Illustrated with Media . In Semantic Web journal (SWJ), Special Issue on Linked Dataset descriptions, 7(2), pages 193-199, 2016.

2015:
Giuseppe Rizzo, Raphaël Troncy, Oscar Corcho, Anthony Jameson, Julien Plu, Juan Carlos Ballesteros Hermida, Ahmad Assaf, Catalin Barbu, Adrian
Spirescu, Kai-Dominik Kuhn, Irene Celino, Rachit Agarwal, Cong Kinh Nguyen, Animesh Pathak, Christian Scanu, Massimo Valla, Timber Haaker,
Emiliano Sergio Verga, Matteo Rossi, José Luis Redondo Garcia.
3cixty@Expo Milano 2015: Enabling Visitors to Explore a Smart City. In 14th International Semantic Web Conference (ISWC’15), Semantic Web
Challenge, Bethlehem, PA, USA, October 11-15, 2015. First Prize Winner

Giuseppe Rizzo, Oscar Corcho, Raphaël Troncy, Julien Plu, Juan Carlos Ballesteros Hermida and Ahmad Assaf. The 3cixty Knowledge Base for Expo
Milano 2015. In 8th International Conference on Knowledge Capture (K-CAP 2015), Short Paper, Palisades, NY, USA, October 7-10, 2015

2014:
Houda Khrouf and Raphaël Troncy. De la modélisation sémantique des événements vers l’enrichissement et la recommandation. In Revue
d’Intelligence Artificielle (RIA), 28(2-3), pages 321-347, 2014.
http://dx.doi.org/10.3166/ria.28.321-347

Houda Khrouf, Vuk Milicic and Raphaël Troncy. Mining Events Connections on the Social Web: Real-Time Instance Matching and Data Analysis in
EventMedia. In Journal of Web Semantics (JWS), 24(1), pages 3-10, 2014.
http://dx.doi.org/10.1016/j.websem.2014.02.003

PasTime:

* Enrico Palumbo, Giuseppe Rizzo and Raphaël Troncy. entity2rec: Learning User-Item Relatedness from Knowledge Graphs for Top-N Item
Recommendation. In 11th ACM International Conference on Recommender Systems (RecSys’17), Como, Italy, August 27-31, 2017
https://doi.org/10.1145/3109859.3109889

* Enrico Palumbo, Giuseppe Rizzo, Raphaël Troncy and Elena Baralis. Predicting Your Next Stop-over from Location-based Social Network Data
with Recurrent Neural Networks. In (RecSys’17) 2nd International Workshop on Recommenders in Tourism (RecTour’17), CEUR Proceedings Vol.
1906, pages 1-8, Como, Italy, August 27-31, 2017