Objective
In the recent years, massive amounts of personal opinions have been posted on the Internet. This allows the companies and institutions to get feedback about their services, provided that they are able to analyse this mass of information.Given that most people prefer to write and read information in their own language, it is clearly relevant to be able to analyse in one language opinions expressed in another language. This is an interdisciplinary topic, called cross-lingual opinion analysis, which involves opinion analysis and machine translation.
Although both topics involved have reached a high maturity level, cross-lingual opinion analysis has been little explored. Most of the work done in this field aimed at leveraging resources in English to perform monolingual opinion analysis in another language.
The objective of this project is to develop a cross-lingual opinion analysis system. To achieve this goal, the fellow will apply his knowledge in machine translation to adapt the monolingual opinion analysis system existing at the host institution. The fellow will develop a novel approach to map across languages concepts such as the opinion target entity, the corresponding attribute and its polarity. This approach consists of enriching the machine translation system with relevant contextual information.
Furthermore several possible architectures of the system will be evaluated and finally a demonstrator will be developed.
The underlying technology will eventually be transferred to the industrial sector, since this is one of the missions of the host institution. Thus the fellow will gain interdisciplinary and inter-sectoral competences.
In addition, European companies will be able to improve their competitiveness. The citizens will be the final beneficiary since companies and public institutions will be able to better take their opinions into account.
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: https://op.europa.eu/en/web/eu-vocabularies/euroscivoc.
CORDIS classifies projects with EuroSciVoc, a multilingual taxonomy of fields of science, through a semi-automatic process based on NLP techniques. See: https://op.europa.eu/en/web/eu-vocabularies/euroscivoc.
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Programme(s)
Multi-annual funding programmes that define the EU’s priorities for research and innovation.
Multi-annual funding programmes that define the EU’s priorities for research and innovation.
Topic(s)
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.
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
Procedure for inviting applicants to submit project proposals, with the aim of receiving EU funding.
Procedure for inviting applicants to submit project proposals, with the aim of receiving EU funding.
FP7-PEOPLE-2011-IEF
See other projects for this call
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
08002 Barcelona
Spain
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.