FashionBrain SIGNED
Understanding Europe’s Fashion Data Universe
Total Cost €
0EC-Contrib. €
0Partnership
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0FashionBrain project word cloud
Explore the words cloud of the FashionBrain project. It provides you a very rough idea of what is the project "FashionBrain" about.
Project "FashionBrain" data sheet
The following table provides information about the project.
| Coordinator |
THE UNIVERSITY OF SHEFFIELD
Organization address contact info |
| Coordinator Country | United Kingdom [UK] |
| Project website | https://fashionbrain-project.eu/ |
| Total cost | 2˙794˙448 € |
| EC max contribution | 1˙699˙323 € (61%) |
| Programme |
1. H2020-EU.2.1.1. (INDUSTRIAL LEADERSHIP - Leadership in enabling and industrial technologies - Information and Communication Technologies (ICT)) |
| Code Call | H2020-ICT-2016-1 |
| Funding Scheme | IA |
| Starting year | 2017 |
| Duration (year-month-day) | from 2017-01-01 to 2019-12-31 |
Partnership
Take a look of project's partnership.
| # | ||||
|---|---|---|---|---|
| 1 | THE UNIVERSITY OF SHEFFIELD | UK (SHEFFIELD) | coordinator | 419˙381.00 |
| 2 | BEUTH-HOCHSCHULE FUER TECHNIK BERLIN | DE (BERLIN) | participant | 591˙667.00 |
| 3 | MONETDB SOLUTIONS BV | NL (AMSTERDAM) | participant | 355˙250.00 |
| 4 | ZALANDO SE | DE (BERLIN) | participant | 333˙025.00 |
| 5 | FASHWELL AG | CH (ZURICH) | participant | 0.00 |
| 6 | UNIVERSITE DE FRIBOURG | CH (FRIBOURG) | participant | 0.00 |
Map
Project objective
The primary goal of each retailer is to “understand your customers”. Our interviews with retailers show a primary demand from the retail industry for predicting a customer's next demand. Surprisingly , even a complete record of past purchases (and returns) is not sufficient to understand how items in a company's catalog do or do not connect with the customer's general tastes, lifestyle and aspirations. Moverover, from a business perspective, any efficiency gains in the logistics of supplier management, shipping and handling are rather minor, compared to the gains one could obtain from a better understanding of the customers’ personalities and habits. Given that the customer demands trigger proactive stocking and fashion production, this appears as a logical consequence. In this project, we want to consolidate and extend existing European technologies in the area of database management, data mining, machine learning, image processing, information retrieval, and crowdsourcing to strengthen the positions of European fashion retailers among their world-wide competitors. Our choice for the fashion sector is a concise one: i) as a multi-billion euro industry, the fashion sector is extremely important for the European economy; ii) Europe already has a solid position in the world fashion stage, however, to maintain its position and keep up with the competitors, European fashion industry needs the help of advanced technology; and iii) European fashion industry provides an excellent exercise for new technologies, because it is a multi-sectorial by itself (i.e., imposes challenging data integration issues), it has a short life-cycle (i.e., requires timely reaction to the current events) and it involves diverse languages and cultures. The main outcome of the FashionBrain project is the improvement of the fashion industry value chain obtained thanks to the creation of novel on-line shopping experiences, the detection of influencers, and the prediction of upcoming fashion trends. Tangible outcomes will include software, demonstrators, and novel algorithms for a data-driven fashion industry.
Deliverables
| Project factsheet | Documents, reports | 2020-04-09 10:55:20 |
| Named Entity Recognition and Linking methods | Other | 2020-04-09 10:55:20 |
| Project Web site | Websites, patent fillings, videos etc. | 2020-04-09 10:55:20 |
| Report on text joins | Documents, reports | 2020-04-09 10:55:20 |
| Early Demo on textual image search | Demonstrators, pilots, prototypes | 2020-04-09 10:55:20 |
| The classification algorithm and its evaluation on fashion time series | Other | 2020-04-09 10:55:20 |
| Demo on Fashion Trend Prediction | Demonstrators, pilots, prototypes | 2020-04-09 10:55:20 |
| Communication plan | Documents, reports | 2020-04-09 10:55:20 |
| Early Demo on Fashion Trend Prediction | Demonstrators, pilots, prototypes | 2020-04-09 10:55:20 |
| Surveys design and crowdsourcing tasks | Documents, reports | 2020-04-09 10:55:20 |
| Relation Extraction with Stacked Deep Learning | Documents, reports | 2020-04-09 10:55:20 |
| Product Taxonomy Linking | Demonstrators, pilots, prototypes | 2020-04-09 10:55:20 |
| Demo on text joins | Demonstrators, pilots, prototypes | 2020-04-09 10:55:19 |
| A set of crowdsourcing interfaces | Other | 2020-04-09 10:55:19 |
| Survey document of existing datasets and data integration solutions (M6) | Documents, reports | 2020-04-09 10:55:20 |
| Scalable Crowdsourced Social Media Annotation | Demonstrators, pilots, prototypes | 2020-04-09 10:55:20 |
| Software Requirements: SSM library for time series modelling and trend prediction | Documents, reports | 2020-04-09 10:55:20 |
| Data integration solution | Other | 2020-04-09 10:55:20 |
| A set of aggregation algorithms and their experimental evaluation | Other | 2020-04-09 10:55:20 |
| Showcase specification | Documents, reports | 2020-04-09 10:55:20 |
Take a look to the deliverables list in detail: detailed list of FashionBrain deliverables.
Publications
| year | authors and title | journal | last update |
|---|---|---|---|
| 2020 |
Ines Arous, Jie Yang, Mourad Khayati and Philippe Cudré-Mauroux OpenCrowd: Leveraging Open-Ended Answers Aggregation for Finding Social Influencers published pages: , ISSN: , DOI: |
2020-04-09 | |
| 2019 |
Rehab Qarout, Alessandro Checco, Gianluca Demartini and Kalina Bontcheva Platform-related Factors in Repeatability and Reproducibility of Crowdsourcing Tasks published pages: , ISSN: , DOI: |
2020-04-09 | |
| 2019 |
Lei Han, Kevin Roitero, Ujwal Gadiraju, Cristina Sarasua, Alessandro Checco, Eddy Maddalena, Gianluca Demartini The Impact of Task Abandonment in Crowdsourcing published pages: 1-1, ISSN: 1041-4347, DOI: 10.1109/tkde.2019.2948168 |
IEEE Transactions on Knowledge and Data Engineering | 2020-04-09 |
| 2018 |
Rehab K. Qarout, Alessandro Checco, Kalina Bontcheva Investigating Stability and Reliability of Crowdsourcing Output published pages: , ISSN: , DOI: |
CrowdBias 2018 | 2020-04-09 |
| 2019 |
Mourad Khayati, Philippe Cudré-Mauroux, Michael H. Böhlen Scalable recovery of missing blocks in time series with high and low cross-correlations published pages: , ISSN: 0219-1377, DOI: 10.1007/s10115-019-01421-7 |
Knowledge and Information Systems | 2020-04-09 |
| 2019 |
Djellel Difallah, Alessandro Checco, Gianluca Demartini, Philippe Cudré-Mauroux Deadline-Aware Fair Scheduling for Multi-Tenant Crowd-Powered Systems published pages: 1-29, ISSN: 2469-7818, DOI: 10.1145/3301003 |
ACM Transactions on Social Computing 2/1 | 2020-04-09 |
| 2020 |
Alessandro Checco, Jo Bates, Gianluca Demartini Adversarial Attacks on Crowdsourcing Quality Control published pages: , ISSN: 1076-9757, DOI: |
Journal of Artificial Intelligence Research | 2020-04-09 |
| 2019 |
Alan Akbik, Tanja Bergmann, Duncan Blythe, Kashif Rasul, Stefan Schweter and Roland Vollgraf FLAIR: An Easy-to-Use Framework for State-of-the-Art NLP published pages: , ISSN: , DOI: |
NAACL-HLT 2019 | 2020-04-09 |
| 2019 |
Alan Akbik, Tanja Bergmann and Roland Vollgraf Multilingual Sequence Labeling With One Model published pages: , ISSN: , DOI: |
NLDL 2019 | 2020-04-09 |
| 2019 |
Alan Akbik, Tanja Bergmann and Roland Vollgraf Pooled Contextualized Embeddings for Named Entity Recognition published pages: , ISSN: , DOI: |
NAACL-HLT 2019 | 2020-04-09 |
| 2018 |
Ying Zhang, Richard Koopmanschap, Martin L. Kersten Love at First Sight: MonetDB/TensorFlow published pages: , ISSN: , DOI: |
34th IEEE International Conference on Data Engineering | 2020-04-09 |
| 2017 |
Ujwal Gadiraju, Alessandro Checco, Neha Gupta, Gianluca Demartini Modus Operandi of Crowd Workers published pages: 1-29, ISSN: 2474-9567, DOI: 10.1145/3130914 |
Proceedings of the ACM on Interactive, Mobile, Wearable and Ubiquitous Technologies 1/3 | 2020-04-09 |
| 2018 |
Alan Akbik, Duncan Blythe and Roland Vollgraf Contextual String Embeddings for Sequence Labeling published pages: , ISSN: , DOI: |
27th International Conference on Computational Linguistics, COLING 2018 | 2020-04-09 |
| 2018 |
Torsten Kilias, Alexander Löpser, Felix A. Gers, Richard Koopmanschap, Ying Zhang, Martin Kersten, Mark Raasveldt, Pedro Holanda, Hannes Mühleisen and Stefan Manegold In-Database Machine Learning with MonetDB/TensorFlow published pages: , ISSN: , DOI: |
2020-04-09 | |
| 2017 |
Alan Akbik, Roland Vollgraf The Projector: An Interactive Annotation Projection Visualization Tool published pages: 43-48, ISSN: , DOI: 10.18653/v1/D17-2008 |
Proceedings of the 2017 Conference on Empirical Methods in Natural Language Processing: System Demonstrations | 2020-04-09 |
| 2018 |
Kilias, Torsten; Löser, Alexander; Gers, Felix A.; Koopmanschap, Richard; Zhang, Ying; Kersten, Martin IDEL: In-Database Entity Linking with Neural Embeddings published pages: 12, ISSN: , DOI: |
1 | 2020-04-09 |
| 2017 |
Alessandro Checco, Kevin Roitero, Eddy Maddalena, Stefano Mizzaro and Gianluca Demartini Let\'s Agree to Disagree: Fixing Agreement Measures for Crowdsourcing published pages: , ISSN: , DOI: |
2020-04-09 | |
| 2018 |
Leonidas Lefakis, Alan Akbik, Roland Vollgraf FEIDEGGER: A Multi-modal Corpus of Fashion Images and Descriptionsin German published pages: , ISSN: , DOI: |
2020-04-09 | |
| 2018 |
Alan Akbik and Roland Vollgraf ZAP: An Open-Source Multilingual Annotation Projection Framework published pages: , ISSN: , DOI: |
11th Language Resources and Evaluation Conference, LREC 2018 | 2020-04-09 |
| 2018 |
Cristina Sarasua, Alessandro Checco, Gianluca Demartini, Djellel Difallah, Michael Feldman, and Lydia Pintscher The Evolution of Power and Standard Wikidata Editors: Comparing Editing Behavior over Time to Predict Lifespan and Volume of Edits published pages: , ISSN: 0925-9724, DOI: |
Computer Supported Cooperative Work (CSCW) Special Issue on Crowd Dynamics: Conflicts, Contradictions, and Cooperation Issues in Crowdsourcing | 2020-04-09 |
| 2017 |
Rudolf Schneider, Tom Oberhauser, Tobias Klatt, Felix A. Gers, and
Alexander Löser RelVis: Benchmarking OpenIE Systems published pages: , ISSN: , DOI: |
International Semantic Web Conference (Posters, Demos & Industry Tracks) 2017 | 2020-04-09 |
| 2018 |
Alessandro Checco, Jo Bates and Gianluca Demartini All That Glitters is Gold - An Attack Scheme on Gold Questions in Crowdsourcing published pages: , ISSN: , DOI: |
The sixth AAAI Conference on Human Computation and Crowdsourcing | 2020-04-09 |
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The information about "FASHIONBRAIN" are provided by the European Opendata Portal: CORDIS opendata.