Cel 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. Dziedzina nauki natural sciencescomputer and information sciencesdata sciencenatural language processingnatural sciencescomputer and information sciencesdata sciencedata miningnatural sciencescomputer and information sciencesartificial intelligencemachine learningdeep learningnatural sciencescomputer and information sciencesdata sciencedata processingnatural sciencescomputer and information sciencesartificial intelligencecomputational intelligence Słowa kluczowe text summarization machine learning natural language processing optimization deep learning Program(-y) H2020-EU.1.3. - EXCELLENT SCIENCE - Marie Skłodowska-Curie Actions Main Programme H2020-EU.1.3.2. - Nurturing excellence by means of cross-border and cross-sector mobility Temat(-y) MSCA-IF-2016 - Individual Fellowships Zaproszenie do składania wniosków H2020-MSCA-IF-2016 Zobacz inne projekty w ramach tego zaproszenia System finansowania MSCA-IF - Marie Skłodowska-Curie Individual Fellowships (IF) Koordynator EIDGENOESSISCHE TECHNISCHE HOCHSCHULE ZUERICH Wkład UE netto € 265 840,20 Adres Raemistrasse 101 8092 Zuerich Szwajcaria Zobacz na mapie Region Schweiz/Suisse/Svizzera Zürich Zürich Rodzaj działalności Higher or Secondary Education Establishments Linki Kontakt z organizacją Opens in new window Strona internetowa Opens in new window Uczestnictwo w unijnych programach w zakresie badań i innowacji Opens in new window sieć współpracy HORIZON Opens in new window Koszt całkowity € 265 840,20 Partnerzy (1) Sortuj alfabetycznie Sortuj według wkładu UE netto Rozwiń wszystko Zwiń wszystko Partner Organizacje partnerskie biorą udział w realizacji działania, jednak nie podpisują umowy o grant. THE REGENTS OF THE UNIVERSITY OF CALIFORNIA Stany Zjednoczone Wkład UE netto € 0,00 Adres FRANKLIN STREET 1111 12 FLOOR 94607 OAKLAND CA Zobacz na mapie Rodzaj działalności Higher or Secondary Education Establishments Linki Kontakt z organizacją Opens in new window Strona internetowa Opens in new window Uczestnictwo w unijnych programach w zakresie badań i innowacji Opens in new window sieć współpracy HORIZON Opens in new window Koszt całkowity € 172 130,40
