Project Achievements

Here you can read more about FashionBrain dissemination activities, publications and reports, and on the prototypes and technologies developed in the project.

Quick Summary


Events Attended

Academic Events

Event
Type
Date
Project representative who attended
34th IEEE International Conference on Data Engineering Conference April 2018 Ying Zhang, Martin Kersten
11TH Extremely Large Databases Conference Conference May 2018 Ying Zhang, Sjoerd Mullender
ACM SIGMOD/PODS International Conference on Management of Data Conference June 2018 Martin Kersten
the 7th International workshop on Testing Database Systems (DBTest) Workshop Jun. 1, 2018 Martin Kersten
The 9th biennial Conference on Innovative Data Systems Research (CIDR) Conference January 2019 Ying Zhang, Martin Kersten
35th IEEE International Conference on Data Engineering (ICDE 2019) Conference April 2019 Svetlin Stalinov
the 2019 ACM SIGMOD/PODS Conference Conference June 2019 Ying Zhang, Martin Kersten
45th International Conference on Very Large Data Bases Conference August 2019 Ying Zhang, Martin Kersten
The sixth AAAI Conference on Human Computation and Crowdsourcing Conference July 2018 Alessandro Checco, Gianluca Demartini
The 41st International ACM SIGIR Conference on Research and Development in Information Retrieval Conference July 2018 Gianluca Demartini
The fifth AAAI Conference on Human Computation and Crowdsourcing Conference October 2017 Alessandro Checco
iConference 2018 Conference March 2018 Alessandro Checco
2017 Workshop on Hybrid Human-Machine Computing (HHMC 2017). Guildford, UK Workshop September 2017 Alessandro Checco
Machine learning meets fashion' workshop at KDD 2017 Workshop August 2017 Alessandro Checco
THE 3RD STRATEGIC WORKSHOP ON INFORMATION RETRIEVAL IN LORNE (SWIRL) Workshop February 2018 Gianluca Demartini
The 28th edition of the Australasian Database Conference, ADC 2017 Conference September 2017 Gianluca Demartini
Australasian Document Computing Symposium Conference December 2017 Gianluca Demartini
Digital Transformation & Global Society (DTGS 2018) Conference June 2017 Gianluca Demartini
2017 Conference on Empirical Methods on Natural Language Processing (EMNLP 2017) Conference September 2017 Alan Akbik, Duncan Blythe
ReWork Machine Learning Summit 2017 Seminar October 2017 Roland Vollgraf
Thirty-first Conference on Neural Information Processing Systems (NIPS 2017) Conference December 2017 Roland Vollgraf
11th Edition of the Language Resources and Evaluation Conference (LREC 2018) Conference May 2018 Alan Akbik
The 27th International Conference on Computational Linguistics (COLING 2018) Conference August 2018 Alan Akbik
LIBER Annual Conference (LIBER 2018) Conference July 2018 Alan Akbik
International Conference on Computer Vision (ICCV 2017) Conference October 2018 Marko Jocic, Matthias Dantone
CrowdBias 2018 Workshop July 2018 Alessandro Checo, Gianluca Demartini
IEEE BigComp2019 Conference March 2019 Alexander Löser (Tutorial Chair)
Second Workshop on Software Foundations for Data Interoperability Workshop February 2019 Alexander Löser (Chair)
35th IEEE International Conference on Data Engineering (ICDE 2019) Conference April 2019 Svetlin Stalinov (demo)
Dagstuhl Seminar on Multi-Document Information Consolidation Seminar April 2019 Sebastian Arnold (speaker)
ACM SIGMOD/PODS International Conference on Management of Data (SIGMOD/PODS 2019) Conference July 2019 Ying Zhang (Industrial track chair), Martin Kersten (General chair)
Data Power 2019 Conference September 2019 Alessandro Checco (speaker)
ACL 2019 Conference July 2019 Sebastian Arnold (speaker)
ACM CIKM 2019 Conference Nov 2019 Benjamin Winter (Speaker), Alexander Löser (Speaker)
HCOMP 2019 Conference October 2019 Alessandro Checco (speaker)
Northern Lights Deep Learning Workshop, NLDL 2019 Workshop February 2019 Alan Akbik
Annual Conference of the North American Chapter of the Association for Computational Linguistics, NAACL 2019 Conference June 2019 Alan Akbik
First symposium on Biases in Human Computation and Crowdsourcing Workshop October 2019 Alessandro Checco (speaker)

Industry Events

Name of Industrial Event
Venue
Big Data, Amsterdam v 6.0Funda, Amsterdam, NLJanuary 2017
Deep Learning for Text Mining Tasks , inovex GmbHHamburg, DEFebruary 2017
Mooc Artificial Intelligence, acatech, CEBITHannover, DEMarch 2017
ACM Distinguished Speaker talkAccenture LatviaApril 2017
Amsterdam Artificial Intelligence & Deep Learning (H2O & Booking.com)Booking.com, Amsterdam, NLApril 2017
Artificial Intelligence Day , Springer NatureBerlin, DEMay 2017
Panel debate Let's talk about Data Products, inovex GmbHCologne, DEMay 2017
Panel Debate Data Products Whats Next, inovex GmbHHamburg, DEMay 2017
"Deep Learning & AI" by Scyfer #1Impact Hub Amsterdam, NLMay 2017
CWI in BedrijfCWI Amsterdam, NLMay 2017
amst-R-dam Simple Imputation and Date Padding CWI Amsterdam, NLMay 2017
Data Products and ExchangeHasso Plattner Insititute, Potsdam, DEJune 2017
Text and data mining(TDM) workshop in European ParliamentBrussels, BEJune 2017
PyData Amsterdam: Data Science week edition @ Flow TradersFlow Traders, Amsterdam, NLJune 2017
Smart Cities 2.0 congresFigi Zeist, NLJune 2017
ADS Drinks & Pizza Summer StartupUvA, Amsterdam, NLJune 2017
ADS Coffee & Data: Visual AnalyticsUvA, Amsterdam, NLJuly 2017
"So how does Tensorflow work?", guest star Siraj RavalGoogle Netherlands, AmsterdamAugust 2017
New challenges in Reinforcement Learning: Dr. O. Vinyals (Google DeepMind)Amsterdam Science Park, NLSeptember 2017
Shoptalk EuropeCopenhagen, DKOctober 2017
European Big Data Value Forum 2017Paris, FRNovember 2017
Data Datives 2017Berlin, DENovember 2017
20e editie Data Donderdag - ING, NS, Growth Tribe, ValuemaatGoDataDriven, Amsterdam, NLNovember 2017
CWI Lectures on Machine LearningCWI Amsterdam, NLNovember 2017
ADS Festive Drinks & Data: 2017 Highlights & Looking Forward to 2018Amsterdam Business School, NLDecember 2017
Influx/DaysLondon, UKJanuary 2018
Handelsblatt goes future: Artifical Intelligence” Conference Munich, DEFebruary 2018
ProductTank Berlin , Data Products Mircosoft, Berlin, DEMarch 2018
SAP Conference on Machine LearningBerlin, DEMarch 2018
ShoptalkLas Vegas, USAMarch 2018
Federal Minisitry of Economics: German Finish Information Exchange Finish Embassy Berlin, DEApril 2018
Brussels TechSummit 2018Brussels, BEJune 2018
K5Berlin, DEJune 2018
AI Expo Europe 2018Amsterdam Rai, NLJune 2018
ADS Drinks & Data Summer StartupAmsterdam Business School, NLJune 2018
FashionTechBerlin, DEJuly 2018
Big Data ExpoUtrecht, NLSeptember 2018
HiPEAC CSW Autumn 2018Heraklion, GROctober 2018
EBDVF 2018Vienna, ATNovember 2018
ACE startup meetingAmsterdam, NLNovember 2018
Meeting organised by Dutch consulate to meet the local Big Data bureau and AI companiesChongQing, CNNovember 2018
HiPEAC, European Network on High Performance and Embedded Architecture and CompilationValencia, SPJanuary, 2019
H2020 Successful R&I in Europe 2019 - 10th European Networking EventDüsseldorf, DEFebruary 2019
Data Warehousing & Business Intelligence summitUtrecht, NLMarch 2019
FOX AI SummitKöln, DEMay 2019
Swedish German Business Days (Swedish Embassy)Berlin, DENovember 2019
Austrian German Business Days (BMVIT and BMWi)Berlin, DENovember 2019
Tagesspiegel 5th Digital Future Science 2019Berlin, DEMarch 2019
Data Warehousing & Business Intelligence summitUtrecht, NLMarch 2019

Other Events

Event
Venue
Date/s
Project representative who attended
Type
Description
Data Science at ASOS.com ASOS.com HQ (London) August 2018 Paul Clough Presentation Presentation of FashionBrain and The University of Sheffield research in Data Science
Startup Qualifiction.com EXIST (BMWi) July 2017 Alexander Löser Startup fundation Text Mining for spotting bestsellers
Startup Beezdata.de BerlinStartupGrant January 2018 Alexander Löser Startup fundation Matching NGOs and Trusts
FashionBrain with projectstarling.com Online September 2018 Alessandro Checco Presentation Presentation of FashionBrain and collaboration plans
Crowdsourcing papers presentation University of Queensland October 2018 Alessandro Checco Presentation Presentation of FashionBrain research in Crowdsourcing
IDEL Paper (D4.3) IEEE BigComp2019 February 2019 Alexander Löser Presentation Best Paper Award (145 submissions, 42 Accepted)
AthNLP 2019 NCSR Demokritos September 2019 Benjamin Winter, Tom Oberhauser Summer School Exchange of information and experience among European NLP researchers

Publications

Academic Publications

Let's Agree to Disagree: Fixing Agreement Measures for Crowdsourcing
Alessandro Checco, Kevin Roitero, Eddy Maddalena, Stefano Mizzaro and Gianluca Demartini
HCOMP 2017
Conference
October 2017
Understanding Engagement through Searching BehaviourMengdie Zhuang, Gianluca Demartini and Elaine TomsCIKM 2017ConferenceNovember 2017
Considering Assessor Agreement in IR EvaluationEddy Maddalena, Kevin Roitero, Gianluca Demartini and Stefano MizzaroICTIR 2017ConferenceOctober 2017
FashionBrain Project: A Vision for Understanding Europe's Fashion Data UniverseAlessandro Checco , Gianluca Demartini, Alexander Löser, Ines Arous, Matthias Dantone, Richard Koopmanschap, Svetlin Stalinov, Martin Kersten, Ying ZhangKDD Fashion 2017Workshophttps://www.overleaf.com/docs/rxrzrqhrwtkj/pdfAugust 2017
The Projector: An Interactive Annotation Projection Visualization ToolAlan Akbik and Roland VollgrafEMNLP 2017Conferencehttp://www.aclweb.org/anthology/D17-2008
ZAP: An Open-Source Multilingual Annotation Projection FrameworkAlan Akbik and Roland VollgrafLREC 2018Conferencehttp://www.lrec-conf.org/proceedings/lrec2018/pdf/301.pdfMay 2018
FEIDEGGER: A Multi-modal Corpus of Fashion Images and Descriptions in GermanLeonidas Lefakis, Alan Akbik and Roland VollgrafLREC 2018Conferencehttp://www.lrec-conf.org/proceedings/lrec2018/pdf/319.pdfMay 2018
Love at First Sight: MonetDB/TensorFlowRichard Koopmanschap, Ying Zhang and Martin KerstenICDE 2018Other
Love at First Sight: MonetDB/TensorFlowRichard Koopmanschap, Ying Zhang and Martin KerstenXLDB2018Other
In-Database Machine Learning with MonetDB/TensorFlowRichard Koopmanschap, Ying Zhang, Martin KerstenXLDB2018Other
On Fine-Grained Relevance ScalesKevin Roitero, Eddy Maddalena, Gianluca Demartini, and Stefano MizzaroSIGIR2018OtherJuly 2018
Investigating User Perception of Gender Bias in Image Search: The Role of SexismJahna Otterbacher, Alessandro Checco, Gianluca Demartini, and Paul CloughSIGIR2018ConferenceJuly 2018
On the Volatility of Commercial Search Engines and its Impact on Information Retrieval ResearchJimmy, Guido Zuccon, and Gianluca DemartiniSIGIR2018OtherJuly 2018
The Evolution of Power and Standard Wikidata Editors: Comparing Editing Behavior over Time to Predict Lifespan and Volume of EditsCristina Sarasua, Alessandro Checco, Gianluca Demartini, Djellel Difallah, Michael Feldman, and Lydia PintscherJournal of CSCWJournalJune 2018
An Introduction to Hybrid Human-Machine Information SystemsGianluca Demartini, Djellel Eddine Difallah, Ujwal Gadiraju, and Michele CatastaFoundation and Trends in Web ScienceOtherDecember 2017
All That Glitters is Gold - An Attack Scheme on Gold Questions in CrowdsourcingAlessandro Checco, Jo Bates, and Gianluca DemartiniHCOMP 2018Conferencehttps://aaai.org/ocs/index.php/HCOMP/HCOMP18/paper/view/17925/16904July 2018
Investigating Stability and Reliability of Crowdsourcing OutputRehab K. Qarout, Alessandro Checco, Kalina BontchevaCrowdBias 2018WorkshopJuly 2018
RelVis: Benchmarking OpenIE SystemsRudolf Schneider, Tom Oberhauser, Tobias Klatt, Felix A. Gers, Alexander LöserISWC 2017Conferencehttp://ceur-ws.org/Vol-1963/paper527.pdfOctober 2017
Analysing Errors of Open Information Extraction SystemsRudolf Schneider, Tom Oberhauser, Tobias Klatt, Felix A. Gers, Alexander LöserEMNLP 2017 WorkshopWorkshophttps://www.aclweb.org/anthology/W17-5402.pdf
Contextual String Embeddings for Sequence LabelingAlan Akbik, Duncan Blythe and Roland VollgradCOLING 2018Conferencehttp://aclweb.org/anthology/C18-1139August 2018
All Those Wasted Hours: On Task Abandonment in CrowdsourcingLei Han, Kevin Roitero, Ujwal Gadiraju, Cristina Sarasua, Alessandro Checco, Eddy Maddalena and Gianluca DemartiniWSDM 2019Conferencehttps://www.researchgate.net/publication/329238136_All_those_wasted_hours_On_task_abandonment_in_crowdsourcingFebruary 2019
IDEL: In-Database Neural Entity LinkingTorsten Kilias, Alexander Löser, Felix A. Gers, Richard Koopmanschap, Ying Zhang and Martin KerstenIEEE BigComp2019Conferencehttp://www.bigcomputing.org/accepted_papers/February 2019
RecovDB: accurate and efficient missing values recovery for large time seriesInes Arous, Mourad Khayati, Philippe Cudré-Mauroux, Ying Zhang, Martin Kersten and Svetlin StalinlovICDE 2019Conferencehttp://conferences.cis.umac.mo/icde2019/April 2019
Pooled Contextualized Embeddings for Named Entity RecognitionAlan Akbik, Tanja Bergmann and Roland VollgrafNAACL-HLT 2019Conferencehttps://www.aclweb.org/anthology/N19-1078/March 2019
Deadline-Aware Fair Scheduling for Multi-Tenant Crowd-Powered SystemsDjellel Difallah, Alessandro Checco, Gianluca Demartini and Philippe Cudré-MaurouxTransactions on Social ComputingJournalhttps://dl.acm.org/citation.cfm?id=3301003January 2019
Implicit Bias in Crowdsourced Knowledge GraphsGianluca DemartiniHumBL-WWW2019WorkshopMay 2019
The Impact of Task Abandonment in CrowdsourcingLei Han, Kevin Roitero, Ujwal Gadiraju, Cristina Sarasua, Alessandro Checco, Eddy Maddalena and Gianluca DemartiniIEEE Transactions on Knowledge and Data Engineering (TKDE)JournalOctober 2019
Platform-related Factors in Repeatability and Reproducibility of Crowdsourcing TasksRehab Qarout, Alessandro Checco, Gianluca Demartini and Kalina BontchevaHCOMP 2019Conferencehttps://www.humancomputation.com/papers.htmlAugust 2019
Scalable recovery of missing blocks in time series with high and low cross-correlationsMourad Khayati, Philippe Cudré-Mauroux and Michael H. BöhlenKAIS 2019Journalhttp://kais.bigke.orgNovember 2019
SECTOR: A Neural Model for Coherent Topic Segmentation and ClassificationSebastian Arnold, Rudolf Schneider, Philippe Cudré-Mauroux, Felix A. Gers, Alexander Löser:TACL 2019Journalhttps://www.mitpressjournals.org/doi/full/10.1162/tacl_a_00261July 2019
FLAIR: An Easy-to-Use Framework for State-of-the-Art NLPAlan Akbik, Tanja Bergmann, Duncan Blythe, Kashif Rasul, Stefan Schweter and Roland VollgrafNAACL-HLT 2019Conferencehttps://www.aclweb.org/anthology/N19-4010/April 2019
Multilingual Sequence Labeling With One ModelAlan Akbik, Tanja Bergmann and Roland VollgrafNLDL 2019Workshophttps://alanakbik.github.io/papers/nldl2019.pdfDecember 2018
Adversarial Attacks on Crowdsourcing Quality ControlAlessandro Checco, Jo Bates, Gianluca DemartiniJournal of Artificial Intelligence Research (JAIR)JournalDecember 2019
OpenCrowd: Leveraging Open-Ended Answers Aggregation for Finding Social InfluencersInes Arous, Jie Yang, Mourad Khayati and Philippe Cudré-MaurouxWWW 2020Conferencehttps://www2020.thewebconf.orgJanuary 2020
Mind the Gap: An Experimental Evaluation of Imputation of Missing Values Techniques in Time SeriesMourad Khayati, Alberto Lerner, Zakhar Tymchenko and Philippe Cudré-MaurouxVLDB 2020Conferencehttp://www.vldb.org/pvldb/vol13/p768-khayati.pdfJanuary 2020

Press Releases/Newsletters

Name
Type
Link
datanami11/04/2019Online newshttps://www.datanami.com/this-just-in/monetdb-solutions-appoints-niels-nes-as-cto/
EEnterpriseAI news10/07/2019Online newshttps://www.enterpriseai.news/2019/10/07/monetdb-solutions-secures-an-investment-from-servicenow-to-help-large-enterprises-drive-digital-transformation-at-scale/
HiPEAC news14/12/2017Online newshttps://www.hipeac.net/press/6829/ten-winners-selected-for-the-2017-hipeac-tech-transfer-awards/
HiPEAC info 5112/07/2017Magazinehttps://www.hipeac.net/assets/public/publications/newsletter/hipeacinfo51_final_corrected.pdf
Computer Weekly07/07/2017Online articlehttp://www.computerweekly.com/news/450422330/Dutch-database-design-drives-practical-innovation
Handelsblatt19/2/18Online articlehttp://veranstaltungen.handelsblatt.com/kuenstliche-intelligenz/2018/03/03/ki-als-enabler/
Beuth-Magazin01/04/2017Cover Storyhttp://www.beuth-hochschule.de/fileadmin/oe/pressestelle/beuth-magazin/2017-1_beuth-magazin.pdf
The University of Sheffield01/05/2017Online articlehttps://www.sheffield.ac.uk/faculty/social-sciences/news/fashion-algorithm-future-trends-project-1.671380
The University of Sheffield15/11/2017Online articlehttps://www.sheffield.ac.uk/is/research/projects/fashionbrain
TagesspiegelOnline newshttps://science-match.tagesspiegel.de/digital-future-2018/speakers/alexander-loser
Exasol MagazineOnline articlehttps://www.exasol.com/en/blog/interactive-text-mining-exasol-indrex-mm/
KI-Berlin01/06/2019Online articlehttps://ki-berlin.de/en/blog/article/prof-dr-alexander-loeser-beuth-university-of-applied-sciences/

Presentations

FashionBrain Project Presentation

Dissemination Material

FashionBrain Factsheet

FashionBrain Project Poster

FashionBrain Project Vision Paper

FashionBrain Project Leaflet

FashionBrain Glossary

Lightening talk at XLDB 2018

FashionBrain description

IDEL In Database Entity Linkage

 

Prototypes and Technologies

Name
Partner(s)
Type
Link
Description
MonetDB with extended windowing functionsApril 2018MDBSsoftwarehttps://www.monetdb.org/DownloadsMonetDB Apr2019 feature release including the extended SQL windowing functions
In-Database Machine LearningApril 2018MDBSsoftwarehttps://github.com/MonetDBMonetDB-Tensorflow integration through SQL Python UDFs which allows executing machine learning tasks inside the kernel of the MonetDB RDBMS
MonetDB continuous query extensionMDBSsoftwarehttps://dev.monetdb.org/hg/MonetDB/shortlog/trailsMonetDB extended with a continuous query processing engine for IoT/Streaming data
MonetDB JSON (renewed)MDBSsoftwarehttps://dev.monetdb.org/hg/MonetDB/shortlog/jsonRenewed support for JSON data loading and processing in MonetDB
RecovDBAugust 2018UNIFR, MDBSsoftwarehttp://revival.exascale.infoIntegration of UNIFR's CD-based technology with MonetDB for missing value recovery in time series
Agreement PhiAugust 2017USFDsoftwarehttp://agreement-measure.sheffield.ac.uk/Source code and live demo of a novel agreement measure for crowdsourcing
Crowdsourcing logging interfaceMay 2018USFDAPIhttps://github.com/AlessandroChecco/herokulogging/Append-only, ephemeral in-memory logging REST interface. https://fast-logging.herokuapp.com/
Gender bias datasetFebruary 2018USFDdatasethttps://github.com/AlessandroChecco/gender_biasDataset used in "Investigating User Bias in Image Search: A Cross-Regional Study". It contains 2,811 query-description comparisons for 281 different users.
Tasty Entity LinkageJune 2018BeuthAPIhttp://demo.datexis.com/tasty/Entity Linkage against Wikipedia
Scalable Crowdsourced Social Media Annotation DemoFashwellAPIhttps://fashionbrain-project.eu/scalable-crowdsourced-social-media-annotation-demo/
Product Taxonomy LinkingFashwellAPIhttps://fashionbrain-project.eu/product-taxonomy-linking/
Demo on Zalando deep learning powered search enginesZalandosoftwarehttps://fashionbrain-project.eu/demo-on-zalando-deep-learning-powered-search-engines/
Tasty feat. IDEL DemonstrationApril 2018Beuthsoftwarehttps://fashionbrain-project.eu/beuth-tasty-feat-idel-demonstration/
BERT Layerwise AnalysisDecember 2019Beuthsoftwarehttps://demo.datexis.com/visbert/We visualize the most important representation BERT for text mining in FashionBrain
Flair release 0.4.4October 2019Zalandosoftwarehttps://github.com/zalandoresearch/flair/releases/tag/v0.4.4Release 0.4.4 of the popular Flair library

Deliverables

D1.1 Survey document of existing datasets and data integration solutions WP1 1 – USFD Report
D1.4 Software Requirements: SSM library for time series modelling and trend prediction WP1 4 – Zalando Report
D2.1 Named Entity Recognition and Linking Methods WP2 3 – UNI FRIBOURG Other
D2.3 Data integration solution WP2 6 – MDBS Other
D2.4 Time Series Operators for MonetDB WP2 6 – MDBS Other
D3.1 A set of crowdsourcing interfaces WP3 1 – USFD Other
D3.2 A set of aggregation algorithms and their experimental evaluation WP3 3 – UNI FRIBOURG Other
D3.3 Pending WP3 1 – USFD Report
D4.1 Report on text joins WP4 2 – BEUTH-HS Report
D4.2 Demo on text join WP4 2 – BEUTH-HS Demonstrator
D4.3 Relation Extraction with Stacked Deep Learning WP4 2 – BEUTH-HS Report
D4.4 Demo on Relation Extraction with Stacked Deep Learning WP4 2 – BEUTH-HS Demonstrator
D5.1 Scalable Crowdsourced Social Media Annotations WP5 5 – Fashwell Demonstrator
D5.2 Social Media Post Linking WP5 5 – Fashwell Demonstrator
D5.3 Early Demo on Fashion Trend Prediction WP5 3 – UNI FRIBOURG Demonstrator
D5.4 The Classification Algorithm and it’s Evaluation on Fashion Time Series WP5 3 – UNI FRIBOURG Other
D5.5 Demo on Fashion Trend Prediction WP5 3 – UNI FRIBOURG Demonstrator
D6.3 Early Demo on Textual Image Search WP6 4 – Zalando Demonstrator