Objective
In our daily life, we are submerged by huge amounts of text, coming from different sources such as emails, news, reports, and so on. The availability of unprecedented volumes of data represents both a challenge and an opportunity. On one hand, it can lead to information overload, a phenomenon that limits one’s capacity to understand an issue and act in the presence of too much information. On the other hand, the effective harnessing of this information has undeniable economical potential. Furthermore, In the European context, special needs to be put to multilingualism to guarantee global access to high quality information.
The objective of this application is to develop ML-TEXTSUM, a system for efficient and accurate multi-lingual text summarization. That is, given as input a text document, the system will output a summary of the document in the same or in a different language. Building on recent breakouts in machine learning and natural language processing, I propose a novel architecture for ML-TEXTSUM that will be able to produce high quality summaries while at same time remain modular enough so that new languages can be added with minimal effort. The availability of such system shall allow citizens, regardless of their language, to better handle the information overload and to gain access to critically distilled information (e.g. what is a certain newspaper’s opinion on the same topic this year? Are male/female athletes portrayed differently by the media?).
The project is characterized by the interplay of multiple disciplines: the proposed architecture requires to master a combination of natural language processing and machine learning techniques. At the same time, the formidable scale of this system will require the development of novel distributed optimization methods. This interplay will be achieved thanks to my past and future collaborations, my solid background in optimization and machine learning, as well as through the acquisition of new ad-hoc skills.
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.
- natural sciences computer and information sciences data science natural language processing
- natural sciences computer and information sciences data science data mining
- natural sciences computer and information sciences artificial intelligence machine learning deep learning
- natural sciences computer and information sciences data science data processing
- natural sciences computer and information sciences artificial intelligence computational intelligence
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Keywords
Project’s keywords as indicated by the project coordinator. Not to be confused with the EuroSciVoc taxonomy (Fields of science)
Project’s keywords as indicated by the project coordinator. Not to be confused with the EuroSciVoc taxonomy (Fields of science)
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.
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H2020-EU.1.3. - EXCELLENT SCIENCE - Marie Skłodowska-Curie Actions
MAIN PROGRAMME
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H2020-EU.1.3.2. - Nurturing excellence by means of cross-border and cross-sector mobility
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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.
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.
MSCA-IF - Marie Skłodowska-Curie Individual Fellowships (IF)
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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.
(opens in new window) H2020-MSCA-IF-2016
See all projects funded under this callCoordinator
Net EU financial contribution. The sum of money that the participant receives, deducted by the EU contribution to its linked third party. It considers the distribution of the EU financial contribution between direct beneficiaries of the project and other types of participants, like third-party participants.
8092 Zuerich
Switzerland
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.