Information retrieval (IR) systems such as Google and Yahoo provide access to different resources available on the World Wide Web (WWW). Usually, current IR systems produce results based on specific keywords and therefore do not take into account user context such as location, browsing history, previous interaction patterns, emotional state and domain expertise. In order to produce accurate search results according to a user’s current needs, it is necessary to investigate search engine personalization for optimization purposes.
The motivation for this special issue is to deepen our understanding of how individual user or user groups’ needs can be supported by personalised information retrieval systems. For example,
- What information about a user’s needs does a system need to be aware of, and how can this be gathered?
- How can this process be automated?
- Can systems adapt to changing user needs, including changes of context and task?
Suitable topics include but are not be limited to:
- Personalised information retrieval
- New interaction techniques and models for information retrieval
- User modelling and information behaviour for information and recommender systems
- Personalised information display, information visualisation, communication of information to the user and HCIR
- Models, theories and algorithms for information system personalisation, implicit and explicit relevance feedback, click through analysis and active learning approaches for the design of information systems
- User studies and ethnographic studies that are relevant to the design of personalised information systems
- Intelligent web search, Web-based adaptive systems, recommender systems
Manuscript due: 28 January, 2011
Notification of acceptance: 29 April, 2011
Revised paper due: 24 June, 2011
Submission of final revised paper: 22 July, 2011