Robotisation of business processes based on artificial intelligence and deep neural networks (Q77723): Difference between revisions
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(Created claim: summary (P836): Reference_reference_programme_aids:SA.41471 (2015/X) _public:Article 25 of Commission Regulation (EC) No 651/2014 of 17 June 2014 declaring certain categories of aid compatible with the internal market in the application of Article 107 and 108 of the Treaty (OJ(OJ LEU L 187/1, 26.06.2014).The aim of the research project will be to provide a solution for the automation of business processes based on unstructured data.The Applica solution will be...) |
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Reference_reference_programme_aids:SA.41471 (2015/X) _public:Article 25 of Commission Regulation (EC) No 651/2014 of 17 June 2014 declaring certain categories of aid compatible with the internal market in the application of Article 107 and 108 of the Treaty (OJ(OJ LEU L 187/1, 26.06.2014).The aim of the research project will be to provide a solution for the automation of business processes based on unstructured data.The Applica solution will be directed primarily at large companies carrying out business processes based on this type of data.The concept of the solution makes it possible to be applied in any subject area, including those that require a level of precision in the processing of data at a level close to 100 %.The idea of the project is to carry out research to implement deep neural networks for the purpose of the solution.This will be one of the first attempts to implement deep neural networks for the processing of natural language for business purposes.This will make it possible to achieve unique functionality on the quality and accuracy of the analysis of the text being processed and on the efficiency of the preparation of such analyses.The project foresees research to adapt the architecture of deep neural networks to the processing of natural language, on tools to retrieve and prepare data for machine learning, the preparation of content models for content, Extranet information and the architecture of the environment for big data processing (big data), and a combination of these with a feedback mechanism allowing self-alignment of solutions and continuous model learning.The project will achieve its 4 research tasks:1 (BP) Data 2.(BP) Data processing 3.(BP) equipment? (English) | |||
Property / summary: Reference_reference_programme_aids:SA.41471 (2015/X) _public:Article 25 of Commission Regulation (EC) No 651/2014 of 17 June 2014 declaring certain categories of aid compatible with the internal market in the application of Article 107 and 108 of the Treaty (OJ(OJ LEU L 187/1, 26.06.2014).The aim of the research project will be to provide a solution for the automation of business processes based on unstructured data.The Applica solution will be directed primarily at large companies carrying out business processes based on this type of data.The concept of the solution makes it possible to be applied in any subject area, including those that require a level of precision in the processing of data at a level close to 100 %.The idea of the project is to carry out research to implement deep neural networks for the purpose of the solution.This will be one of the first attempts to implement deep neural networks for the processing of natural language for business purposes.This will make it possible to achieve unique functionality on the quality and accuracy of the analysis of the text being processed and on the efficiency of the preparation of such analyses.The project foresees research to adapt the architecture of deep neural networks to the processing of natural language, on tools to retrieve and prepare data for machine learning, the preparation of content models for content, Extranet information and the architecture of the environment for big data processing (big data), and a combination of these with a feedback mechanism allowing self-alignment of solutions and continuous model learning.The project will achieve its 4 research tasks:1 (BP) Data 2.(BP) Data processing 3.(BP) equipment? (English) / rank | |||
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Revision as of 08:54, 4 March 2020
Project in Poland financed by DG Regio
Language | Label | Description | Also known as |
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English | Robotisation of business processes based on artificial intelligence and deep neural networks |
Project in Poland financed by DG Regio |
Statements
9,928,108.01 zloty
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12,845,759.94 zloty
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3,082,982.3855999997 Euro
0.24 Euro
13 January 2020
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77.29 percent
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1 October 2017
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31 March 2021
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APPLICA SPÓŁKA Z OGRANICZONĄ ODPOWIEDZIALNOŚCIĄ
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Numer_referencyjny_programu_pomocowego: SA.41471(2015/X) Przeznaczenie_pomocy_publicznej: art. 25 rozporządzenia KE nr 651/2014 z dnia 17 czerwca 2014 r. uznające niektóre rodzaje pomocy za zgodne z rynkiem wewnętrznym w stosowaniu art. 107 i 108 Traktatu (Dz. Urz. UE L 187/1 z 26.06.2014). Celem projektu badawczego będzie stworzenie rozwiązania do automatyzacji procesów biznesowych opartych o dane nieustrukturyzowane. Rozwiązanie Applica będzie skierowane przede wszystkim do dużych przedsiębiorstw, realizujących procesy biznesowe oparte o dane tego rodzaju. Koncepcja rozwiązania sprawia, że będzie ono mogło zostać zastosowane w dowolnym obszarze tematycznym, także w procesach, w których wymagany jest poziom precyzji przy przetwarzaniu danych na poziomie bliskim 100%. Koncepcja projektu zakłada realizację prac badawczych mających na celu implementację głębokich sieci neuronowych na potrzeby rozwiązania. Będzie to jedna z pierwszych prób takiej implementacji głębokich sieci neuronowych do przetwarzania języka naturalnego na potrzeby biznesowe. Umożliwi to osiągnięcie unikalnych funkcjonalności w zakresie jakości i dokładności analizy przetwarzanego tekstu oraz efektywności przygotowania takich analiz. W ramach projektu przewidziano prace badawcze nad dostosowaniem architektury głębokich sieci neuronowych do przetwarzania języka naturalnego, nad narzędziami do pozyskiwania i przygotowania danych na potrzeby uczenia maszynowego, przygotowaniem modeli klasyfikatorów treści, ekstraktorów informacji oraz architektury środowiska do strumieniowego przetwarzania dużych wolumenów danych (big data) oraz połączenie tych elementów z wykorzystaniem mechanizmu sprzężenia zwrotnego umożliwiającego autokorektę rozwiązania i stałe uczenie modeli. Cel projektu zostanie osiągnięty dzięki realizacji 4 zadań badawczych: 1 (BP) Pozyskanie danych 2. (BP) Przetwarzanie danych 3. (BP) Sprzę? (Polish)
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Reference_reference_programme_aids:SA.41471 (2015/X) _public:Article 25 of Commission Regulation (EC) No 651/2014 of 17 June 2014 declaring certain categories of aid compatible with the internal market in the application of Article 107 and 108 of the Treaty (OJ(OJ LEU L 187/1, 26.06.2014).The aim of the research project will be to provide a solution for the automation of business processes based on unstructured data.The Applica solution will be directed primarily at large companies carrying out business processes based on this type of data.The concept of the solution makes it possible to be applied in any subject area, including those that require a level of precision in the processing of data at a level close to 100 %.The idea of the project is to carry out research to implement deep neural networks for the purpose of the solution.This will be one of the first attempts to implement deep neural networks for the processing of natural language for business purposes.This will make it possible to achieve unique functionality on the quality and accuracy of the analysis of the text being processed and on the efficiency of the preparation of such analyses.The project foresees research to adapt the architecture of deep neural networks to the processing of natural language, on tools to retrieve and prepare data for machine learning, the preparation of content models for content, Extranet information and the architecture of the environment for big data processing (big data), and a combination of these with a feedback mechanism allowing self-alignment of solutions and continuous model learning.The project will achieve its 4 research tasks:1 (BP) Data 2.(BP) Data processing 3.(BP) equipment? (English)
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Identifiers
POIR.01.01.01-00-0144/17
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