SeRSy 2013 - 2nd International Workshop on Recommender Systems meet Big Data & Semantic Technologies

More and more semantic data are published following the Linked Data principles, that enable to set up links between objects in different data sources, by connecting information in a single global data space ? the Web of Data. Today, Web of Data includes different types of knowledge represented in a homogeneous form ? sedimentary one (encyclopedic, cultural, linguistic, common-sense and real-time one (news, data streams. This data might be useful to interlink diverse information about users, items, and their relations and implement reasoning mechanisms that can support and improve the recommendation process.
The challenge is to investigate whether and how this large amount of wide-coverage and linked semantic knowledge can significantly improve complex search and filtering tasks that cannot be solved merely through a straightforward matching of queries (or user profiles) and items. Such tasks involve finding information from large document collections, categorizing and understanding that information, and producing some output, such as an actionable decision. Examples of such tasks include understanding a health problem in order to make a medical decision, or simply deciding which laptop to buy. Recommender systems support users exactly in those complex tasks.
ORGANIZERS
Marco de Gemmis (University of Bari Aldo Moro, Italy)
Tommaso Di Noia (Polytechnic University of Bari, Italy)
Ora Lassila (Nokia Research Center, Cambridge, Massachusetts, U.S.)
Pasquale Lops (University of Bari Aldo Moro, Italy)
Thomas Lukasiewicz (University of Oxford, UK)
Giovanni Semeraro (University of Bari Aldo Moro, Italy)
WORKSHOP DATE
October 13, 2013
WEB SITE
http://sisinflab.poliba.it/sersy2013/