Bibliographie - Données massives, apprentissage automatique et éthique

@inproceedings{yang2013turn, title={Turn on, tune in, drop out: Anticipating student dropouts in massive open online courses}, author={Yang, Diyi and Sinha, Tanmay and Adamson, David and Ros{\'e}, Carolyn Penstein} }

@inproceedings{han2011survey, title={Survey on NoSQL database}, author={Han, Jing and Haihong, E and Le, Guan and Du, Jian}, booktitle={Pervasive computing and applications (ICPCA), 2011 6th international conference on}, pages={363--366}, year={2011}, organization={IEEE} }

@article{moniruzzaman2013nosql, title={Nosql database: New era of databases for big data analytics-classification, characteristics and comparison}, author={Moniruzzaman, ABM and Hossain, Syed Akhter}, journal={arXiv preprint arXiv:1307.0191}, year={2013} }

@article{angles2008survey, title={Survey of graph database models}, author={Angles, Renzo and Gutierrez, Claudio}, journal={ACM Computing Surveys (CSUR)}, volume={40}, number={1}, pages={1}, year={2008}, publisher={ACM} }

@article{berners2001semantic, title={The semantic web}, author={Berners-Lee, Tim and Hendler, James and Lassila, Ora}, journal={Scientific american}, volume={284}, number={5}, pages={34--43}, year={2001}, publisher={JSTOR} }

@article{chang2008bigtable, title={Bigtable: A distributed storage system for structured data}, author={Chang, Fay and Dean, Jeffrey and Ghemawat, Sanjay and Hsieh, Wilson C and Wallach, Deborah A and Burrows, Mike and Chandra, Tushar and Fikes, Andrew and Gruber, Robert E}, journal={ACM Transactions on Computer Systems (TOCS)}, volume={26}, number={2}, pages={4}, year={2008}, publisher={ACM} }

@inproceedings{manning2014stanford, title={The Stanford CoreNLP natural language processing toolkit}, author={Manning, Christopher and Surdeanu, Mihai and Bauer, John and Finkel, Jenny and Bethard, Steven and McClosky, David}, booktitle={Proceedings of 52nd annual meeting of the association for computational linguistics: system demonstrations}, pages={55--60}, year={2014} }

@article{sivic2009efficient, title={Efficient visual search of videos cast as text retrieval}, author={Sivic, Josef and Zisserman, Andrew}, journal={IEEE transactions on pattern analysis and machine intelligence}, volume={31}, number={4}, pages={591--606}, year={2009}, publisher={IEEE} }

@article{vinyals2017show, title={Show and tell: Lessons learned from the 2015 mscoco image captioning challenge}, author={Vinyals, Oriol and Toshev, Alexander and Bengio, Samy and Erhan, Dumitru}, journal={IEEE transactions on pattern analysis and machine intelligence}, volume={39}, number={4}, pages={652--663}, year={2017}, publisher={IEEE} }

@article{doi:10.1080/00031305.1973.10478966, author = { F. J. Anscombe }, title = {Graphs in Statistical Analysis}, journal = {The American Statistician}, volume = {27}, number = {1}, pages = {17-21}, year = {1973}, publisher = {Taylor & Francis}, doi = {10.1080/00031305.1973.10478966}, URL = {}, eprint = {} }

@article{terveen2001beyond, title={Beyond recommender systems: Helping people help each other}, author={Terveen, Loren and Hill, Will}, journal={HCI in the New Millennium}, volume={1}, number={2001}, pages={487--509}, year={2001}, publisher={Addison-Wesley, Reading, MA} }

@inproceedings{nguyen2014exploring, title={Exploring the filter bubble: the effect of using recommender systems on content diversity}, author={Nguyen, Tien T and Hui, Pik-Mai and Harper, F Maxwell and Terveen, Loren and Konstan, Joseph A}, booktitle={Proceedings of the 23rd international conference on World wide web}, pages={677--686}, year={2014}, organization={ACM} }

@article{doi:10.1177/2053951714541861, author = {David Lyon}, title ={Surveillance, Snowden, and Big Data: Capacities, consequences, critique}, journal = {Big Data \& Society}, volume = {1}, number = {2}, pages = {2053951714541861}, year = {2014}, doi = {10.1177/2053951714541861},

URL = {

}, eprint = {

} , abstract = { The Snowden revelations about National Security Agency surveillance, starting in 2013, along with the ambiguous complicity of internet companies and the international controversies that followed provide a perfect segue into contemporary conundrums of surveillance and Big Data. Attention has shifted from late C20th information technologies and networks to a C21st focus on data, currently crystallized in “Big Data.” Big Data intensifies certain surveillance trends associated with information technology and networks, and is thus implicated in fresh but fluid configurations. This is considered in three main ways: One, the capacities of Big Data (including metadata) intensify surveillance by expanding interconnected datasets and analytical tools. Existing dynamics of influence, risk-management, and control increase their speed and scope through new techniques, especially predictive analytics. Two, while Big Data appears to be about size, qualitative change in surveillance practices is also perceptible, accenting consequences. Important trends persist – the control motif, faith in technology, public-private synergies, and user-involvement – but the future-orientation increasingly severs surveillance from history and memory and the quest for pattern-discovery is used to justify unprecedented access to data. Three, the ethical turn becomes more urgent as a mode of critique. Modernity's predilection for certain definitions of privacy betrays the subjects of surveillance who, so far from conforming to the abstract, disembodied image of both computing and legal practices, are engaged and embodied users-in-relation whose activities both fuel and foreclose surveillance. } }

@inproceedings{ribeiro2016should, title={Why should i trust you?: Explaining the predictions of any classifier}, author={Ribeiro, Marco Tulio and Singh, Sameer and Guestrin, Carlos}, booktitle={Proceedings of the 22nd ACM SIGKDD International Conference on Knowledge Discovery and Data Mining}, pages={1135--1144}, year={2016}, organization={ACM} }

@article{garcia2006simap, title={SIMAP: Intelligent System for Predictive Maintenance: Application to the health condition monitoring of a windturbine gearbox}, author={Garcia, Mari Cruz and Sanz-Bobi, Miguel A and del Pico, Javier}, journal={Computers in Industry}, volume={57}, number={6}, pages={552--568}, year={2006}, publisher={Elsevier} }

@inproceedings{zhang2016road, title={Road crack detection using deep convolutional neural network}, author={Zhang, Lei and Yang, Fan and Zhang, Yimin Daniel and Zhu, Ying Julie}, booktitle={Image Processing (ICIP), 2016 IEEE International Conference on}, pages={3708--3712}, year={2016}, organization={IEEE} }

@article{el2014artificial, title={Artificial neural network models for predicting condition of offshore oil and gas pipelines}, author={El-Abbasy, Mohammed S and Senouci, Ahmed and Zayed, Tarek and Mirahadi, Farid and Parvizsedghy, Laya}, journal={Automation in construction}, volume={45}, pages={50--65}, year={2014}, publisher={Elsevier} }

@inproceedings{menk2015hybrid, title={A hybrid recommendation system based on human curiosity}, author={Menk dos Santos, Alan}, booktitle={Proceedings of the 9th ACM Conference on Recommender Systems}, pages={367--370}, year={2015}, organization={ACM} }