Project description
Cognitive Systems, Interaction, Robotics
Eye movements can be used as input for search engines
Simple search engines have turned out to be successful in text retrieval. This is partly due to advances in algorithms, but additionally because the typical tasks are relatively straightforward as it is possible to come up with a good list of keywords with a reasonable effort. All information needs cannot however be solved with such searches. For the more and more commonly available audio-visual data people are not able to specify efficient non-textual search keys. Moreover, if the information needs of the user are tacit it is very laborious to create a query.We develop new information retrieval principles needed for replacing or complementing explicit queries. The new techniques will be applied to construct prototypes of proactive information navigators, the next generation systems able to adapt to the user and her tacit information needs. During browsing and searching with a task-dependent interface, the goals of the user will be inferred from implicit feedback signals and interaction, complemented with social filtering.New advanced machine learning methods are needed for inferring the implicit topic of interest and the sense in which it is interesting. We will augment the standard two-valued relevance feedback from the user by richer feedback derived from point-and-click and point-and-speak interfaces and gaze patterns over items that include texts, images and movies. Eye tracking technology is rapidly maturing to be usable on a massive scale.Our consortium combines pioneering application expertise with solid machine learning background. We have built a top content-based image retrieval system and used eye tracking in information retrieval. Our machine learning expertise is suited for the core issues of learning the comparison metrics and solving the exploration-exploitation problem. Proactive information navigators will bring up a new spectrum of application areas; the system will be tested in a set of targeted applications by two industry partners.
Fields of science (EuroSciVoc)
CORDIS classifies projects with EuroSciVoc, a multilingual taxonomy of fields of science, through a semi-automatic process based on NLP techniques. See: The European Science Vocabulary.
CORDIS classifies projects with EuroSciVoc, a multilingual taxonomy of fields of science, through a semi-automatic process based on NLP techniques. See: The European Science Vocabulary.
- humanities arts modern and contemporary art cinematography
- natural sciences computer and information sciences artificial intelligence machine learning
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Programme(s)
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Multi-annual funding programmes that define the EU’s priorities for research and innovation.
Topic(s)
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Calls for proposals are divided into topics. A topic defines a specific subject or area for which applicants can submit proposals. The description of a topic comprises its specific scope and the expected impact of the funded project.
Call for proposal
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Procedure for inviting applicants to submit project proposals, with the aim of receiving EU funding.
FP7-ICT-2007-1
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Funding Scheme
Funding scheme (or “Type of Action”) inside a programme with common features. It specifies: the scope of what is funded; the reimbursement rate; specific evaluation criteria to qualify for funding; and the use of simplified forms of costs like lump sums.
Funding scheme (or “Type of Action”) inside a programme with common features. It specifies: the scope of what is funded; the reimbursement rate; specific evaluation criteria to qualify for funding; and the use of simplified forms of costs like lump sums.
Coordinator
02150 Espoo
Finland
The total costs incurred by this organisation to participate in the project, including direct and indirect costs. This amount is a subset of the overall project budget.