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2011 Proceeding- Conference Chairs:
- Ernesto W. De Luca,
- Alan Said,
- Matthias Böhmer,
- Florian Michahelles
The aim of the CaRR workshop was to invite the community to a discussion on new, creative ways to handle context-awareness. Furthermore, the workshop aimed at improving the exchange of ideas between different communities involved in research concerning machine learning, information retrieval and recommendation.
The workshop was intended for researchers working on multidisciplinary tasks who wanted to discuss problems and synergies. The focus of the workshop was on creative and collaborative approaches for context-aware retrieval and recommendation.
Proceeding Downloads
Innovative Retail Laboratory: assistive technologies in retail environments
In this talk I will present different lines of research which we pursue in the Innovative Retail Laboratory (IRL) at DFKI. IRL is a joint venture of the German retailer GLOBUS, DFKI and Saarland University. The focus lies on user-centric assistive ...
Towards a context-sensitive online newspaper
We give a detailed account of our experiences in implementing a personalized online newspaper that draws---among other hints---on the context of the user. At the algorithmic core of our framework lies a machine learning model that incorporates numerous ...
Implicit acquisition of context for personalization of information retrieval systems
One major problem of most current information retrieval systems is that they provide uniform access and retrieval results to all users solely based on the query terms users issued to the system. In this paper, we propose a model to personalize the ...
Real-time, location-aware collaborative filtering of web content
In this paper we describe the collaborative filtering feature of a location-aware, Web content recommendation service, called Gloe. The main purpose of our collaborative filtering solution is to increase the diversity of recommendations and to thereby ...
Utilizing implicit feedback and context to recommend mobile applications from first use
Most mobile platforms of today enable the users to install third-party applications through application portals or stores. As the number of applications available increases, the users of mobile devices find it challenging to find new and relevant ...
Context-aware POI recommendations in an automotive scenario using multi-criteria decision making methods
Recommender systems are commonly used for recommending items such as products, restaurants or other points-of-interest (POI). In our automotive scenario, the driver of a car gets recommendations for gas stations. Thereby, item attributes such as price ...
RecLab: a system for eCommerce recommender research with real data, context and feedback
In this paper we introduce RecLab, a system designed to enable developers to build and test recommendation algorithms for eCommerce websites. RecLab supports a variety of context and feedback that recommenders can take advantage of to improve the ...
OSUSUME: cross-lingual recommender system for research papers
In this paper, we introduce a cross-lingual recommender system for research papers based on multiple-facets in Japanese. The system is the first Japanese research paper recommender system and recommends international papers simply by typing Japanese ...
Designing activity-aware recommender systems for operating rooms
This paper presents research in ubiquitous computing focusing on creating context- and activity-aware systems in collaborative environments such as hospitals. These activity-aware systems are able to infer human physical actions and subsequently offer ...
Guidance and support for healthy food preparation in an augmented kitchen
An important barrier to healthful eating is a lack of cooking competence. To assist people who are motivated to increase their cooking competence, we envision a context-aware kitchen that offers a recipe retrieval and recommendation system. Preceding ...
