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КартаВръзкиТемиБългарияНощта (K-TRIO)Мария Склодовска-КюриЗа ученициЗа учителиМетодологияИзненадай ме
H2020Докторантска мрежа2015–2018

WDAqua · Answering Questions using Web Data

„Хоризонт 2020“ — Действия „Мария Склодовска-Кюри“

Период
2015-01-01 → 2018-12-31
Финансиране от ЕС
3 885 922 €
Участници
13
Схема
MSCA-ITN

Линиите свързват координатора с партньорите.

Накратко на български

Системите за автоматично отговаряне на въпроси използват данни от мрежата, за да разберат естествен език и да предоставят точни отговори. Това помага за създаването на по-добри услуги за гражданите и индустрията чрез по-лесен достъп до информацията.

Този кратък обзор е генериран от изкуствен интелект

Кратко обяснение, генерирано от езиков модел по текста на CORDIS. Оригиналът е по-долу.

Резултати накратко

Answering Questions using Web Data

Sharing, connecting, analysing, and understanding data on the Web can provide better services to citizens, communities, and the industry. One way to achieve this is through data-driven question answering, by delivering precise and comprehensive answers to natural language questions, primarily by making better use of the knowledge encoded in the Web of Data. The aim of the WDAqua project was to advance the state of the art in this field by interleaving training, research, and innovation. The WDAqua project: - Provided a training programme for young data scientists - Addressed challenges related to the whole question answering pipeline including 1) understanding of a spoken question, 2) analysis of the question, 3) retrieval of information to answer the question, and 4) presentation of the answer - Delivered an open source framework and ecosystem of question answering components The main research challenges addressed in the project can be summarized in the following points: - Answer questions expressed in different formats - Exploit knowledge encoded in the Web of Data to enhance question answering - Scale question answering to the size and dynamicity of the Web - Provide comprehensible answers for questions and justifications for these answers - Consider trust and provenance, as well as data access control during question answering - Discover high-quality datasets suitable for question answering, including cross-lingual, cross-border, and cross-domain settings - Enable users to easily ask questions and find answers Fifteen excellent international Early Stage Researchers (ESRs) have worked on research projects addressing these challenges and have developed several collaborations inside and outside the network. In an interdisciplinary and intersectoral research environment, the ESRs have received high-quality training including 3 R&D Weeks, 3 Learning Weeks, one Innovation Week and various workshops as well as the participation to international scientific conferences and workshops, academic and soft skills courses and accomplishment of industrial and academic secondments. In the four years of the project duration, the young researchers managed to develop their individual skills for pursuing a successful career in academia and industry, as well as to build a strong network, capable of advancing the state of the art in Question Answering over the Web of Data.

Текст от CORDIS, на английски · Данни: CORDIS, © Европейски съюз

Цел на проекта

The H2020 work programme aims at increasing citizens’ participation in the digital society and making infrastructures“smart”. These processes are increasingly data-driven. Our central motivation is that sharing, connecting,managing, analysing and understanding data on the Web will enable better services for citizens, communities andindustry. However, turning web data into successful services for the public and private sector requires skilled weband data scientists, and it still requires further research. WDAqua aims at advancing the state of the art by intertwiningtraining, research and innovation efforts, centered around one service: data-driven question answering.Question answering is immediately useful to a wide audience of end users, and we will demonstrate this in settingsincluding e-commerce, public sector information, publishing and smart cities. Question answering also coversweb science and data science broadly, leading to transferrable research results and to transferrable skills ofthe researchers who have finished our training programme.To ensure that our research improves question answering overall, we require every individual research project to connect at least two steps of the question answering process.Intersectoral secondments (within a consortium covering academia, research institutes and industrial research)as well as network-wide workshops, R&D challenges and innovation projects further balance groundbreakingresearch and the needs of society and industry. Training-wise these offers equip ESRs with the expertiseand transferable technical and non-technical skills that will allow them to pursue a successful career as an academic,decision maker, practitioner or entrepreneur. Our research programme capitalizes on previous researchexcellence of the beneficiaries; the training programme builds on the excellent local programs of the academicbeneficiaries, as well as on a significant commitment from non-academic partners to management.

Оригинален текст от CORDIS (на английски).

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Връзки

Данни: CORDIS, © Европейски съюз