=Paper=
{{Paper
|id=None
|storemode=property
|title=Contextualizing Recommendations
|pdfUrl=https://ceur-ws.org/Vol-889/keynote.pdf
|volume=Vol-889
}}
==Contextualizing Recommendations==
<pdf width="1500px">https://ceur-ws.org/Vol-889/keynote.pdf</pdf>
<pre>
                             Contextualizing Recommendations
                                                          Francesco Ricci
                                                      Free University of Bozen-
                                                           Bolzano, Italy
                                                           fricci@unibz.it




ABSTRACT
State of the art recommendation techniques still cannot fully explain and predict the information needs of the user while is searching for
items such as news, services or products. In fact, the specific ephemeral needs of the user, the context of the search, and the context of
items’ usage, do influence the user’s response to, and evaluation for items. Hence, RSs should take into account this information to deliver
recommendations that users would judge as appropriate to their situations. Context modeling and context-dependent reasoning is a complex
subject and there are still major technical and practical difficulties to solve: obtain sufficient and reliable data describing the user prefer-
ences in context; selecting the right contextual information, i.e., relevant in a particular personalization task; understanding the impact of
the contextual dimensions on the user decision making process; embedding the contextual dimensions in a recommendation computational
model. These topics will be illustrated in the talk, making examples taken from the recommender systems that we have developed.

ABOUT THE KEYNOTE SPEAKER
Francesco Ricci is associate professor of computer science at the Free University of Bozen-Bolzano, Italy. His current research interests
include recommender systems, intelligent interfaces, mobile systems, machine learning, case-based reasoning, and the applications of ICT
to tourism. He has published more than one hundred of academic papers on these topics. He is on the editorial board of Journal of Infor-
mation Technology & Tourism and the Journal of User Modeling and User Adapted Interaction. He is member of the steering committee of
the ACM Conference on Recommender Systems. He served on the program committees of several conferences, including as a program co-
chair of the ACM Conference on Recommender Systems (RecSys), the International Conference on Case-Based Reasoning (ICCBR) and
the International Conference on Information and Communication Technologies in Tourism (ENTER).




Copyright is held by the author/owner(s).
RecSys’12, September 9–13, 2012, Dublin, Ireland.

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