Contents and Main Goals
Context-aware information is widely available in various ways such as interaction patterns, location, devices, annotations, query suggestions and user profiles and is becoming more and more important for enhancing retrieval performance and recommendation results. At the moment, the main issue to cope with is not only recommending or retrieving the most relevant items and content, but defining them ad hoc. Further relevant issues are personalizing and adapting the information and the way it is displayed to the user’s current situation (device, location) and interests. In this workshop we want to focus on the integration of context for retrieval and recommendation. We recognize a general content context and a user-centric content context. A general content context is a common case defined by time, weather, location and many similar other aspects. A user-centric content context is given by the content of user profiles such as language, interests, devices used for interaction, etc.
Another important issue to address is the importance of developing context-aware systems that can generate and present situation-specific information. The need of personalizing and adapting information is accentuated when we consider this kind of device- and interaction-based context.
The aim of the CaRR Workshop is to invite the community to a discussion in which we will try to find new creative ways to handle context-awareness. Furthermore, the workshop aims at improving the exchange of ideas between different communities involved in research concerning, among other machine learning, information retrieval and recommendation.
The workshop is especially intended for researchers working on multidisciplinary tasks who want to discuss problems and synergies. We are interested in ideas about creative and collaborative approaches for context-aware retrieval and recommendation.
The participants are encouraged to address the following questions:
- What is context?
- Is context-awareness in retrieval and recommendation necessary?
- Which benefits come from context-aware retrieval and recommendation systems?
- How do user interfaces handle context?
- In what ways can context improve HCI?
- How can we combine general- and user-centric context-aware technologies?
- How should context affect the way information is presented?
The topics of interest include, but are not limited to, the following aspects:
- Context-aware information retrieval
- Context-aware profiling, clustering and collaborative filtering
- Machine learning for context-aware information retrieval and ontology learning
- Ubiquitous and context-aware computing
- Use of context-aware technologies in UI/HCI
- Context-aware advertising
- Recommendations for mobile users
- Context-awareness in portable devices
Please also see last Call for Papers.