C. Gutierrez, Survey of graph database models, Proc. of European Semantic Web Conf. (ESWC), pp.346-3601, 2005.

M. Jesús, A. Almendros-jiménez, G. Luna, and . Moreno, A Flexible XPath-based Query Language Implemented with Fuzzy Logic Programming, Proc. of the Intl. Conf. on Rule-based Reasoning, Programming, and Applications (RuleML), pp.186-193

. Springer-verlag, A comparison of current graph database models [AP11] Marcelo Arenas and Jorge Pérez. Querying semantic web data with SPARQL, Proc. of IEEE Intl. Conf. on Data Engineering Workshops Proc. of the ACM Symposium on Principles of Database Systems (PODS)BB13] Pablo Barceló Baeza. Querying graph databases Proc. of the ACM Symposium on Principles of Database Systems (PODS)BDBH08] Patrice Buche, Juliette Dibie-Barthélemy, and Gaëlle Hignette. Flexible Querying of Fuzzy RDF Annotations Using Fuzzy Conceptual Graphs Proc. of Intl. Conf. on Conceptual Structures (ICCS) SQLf: a relational database language for fuzzy querying, pp.171-177, 2008.

P. Bosc and O. Pivert, On four noncommutative fuzzy connectives and their axiomatization. Fuzzy Sets and Systems An algorithm to compute the supremum of max-min powers and a property of fuzzy graphs Comparative analysis of relational and graph databases Benchmarking traversal operations over graph databases A Fuzzy Extension of the XPath Query Language, 2012. [CAH12] Marek Ciglan, Alex Averbuch, and Ladislav Hluch´yHluch´y IEEE ICDE Workshops, pp.1-1742, 1991.
URL : https://hal.archives-ouvertes.fr/hal-00736339

J. Cheng, Z. M. Ma, and L. Yan, f-SPARQL: A Flexible Extension of SPARQL, Proc. of the Intl. Conf. on Database and Expert Systems Applications, pp.487-494, 2010.
DOI : 10.1007/978-3-642-15364-8_41

P. Juan, K. Cedeño, and . Selçuk-candan, R2DF Framework for Ranked Path Queries over Weighted RDF Graphs FuzzyXPath: Using Fuzzy Logic an IR Features to Approximately Query XML Documents, Proc. of the Intl. Conf. on Web Intelligence, Mining and Semantics Foundations of Fuzzy Logic and Soft Computing, pp.1-40, 2011.

D. Springer-didier and H. Prade, Weighted minimum and maximum operations in fuzzy set theory Using fuzzy sets in database systems: Why and how? of The Handbooks of Fuzzy Sets, Proc. of FQAS'96DP00] Didier Dubois and Henri Prade. Fundamentals of fuzzy sets, pp.205-210, 1986.

D. Dominguez-sal, P. Urbón-bayes, A. Giménez-vañó, S. Gómez-villamor, N. Martínez-bazan et al., Survey of Graph Database Performance on the HPC Scalable Graph Analysis Benchmark Adding regular expressions to graph reachability and pattern queries Fuzzy-set theoretic operators and quantifiers Graphgrep: A fast and universal method for querying graphs Graphs-at-a-time: query language and access methods for graph databases, Proc. of WAIM'10 WorkshopsFLM + 12] Wenfei Fan, The Handbooks of Fuzzy Sets Series Fundamentals of Fuzzy Sets Proc. of SIGMOD'08HWYY07] Hao He, Haixun Wang, Jun Yang, and Philip S. 6. REFERENCES [1] A.Elsayed, O.Ismail, and M.E.El-Sharkawin, pp.37-48313, 2000.

A. Thusoo, J. S. Sarma, N. Jain, Z. Shao, P. Chakka et al., Hive, Proceedings of the VLDB Endowment, pp.1626-1629, 2009.
DOI : 10.14778/1687553.1687609

B. Arres, N. Kabbachi, and O. Boussaid, Building OLAP cubes on a Cloud Computing environment with MapReduce, 2013 ACS International Conference on Computer Systems and Applications (AICCSA), pp.1-5, 2013.
DOI : 10.1109/AICCSA.2013.6616498
URL : https://hal.archives-ouvertes.fr/hal-00907004

C. Doulkeridis and K. Norvagl, A survey of large-scale analytical query processing in MapReduce, The VLDB Journal, vol.21, issue.5, pp.355-380, 2014.
DOI : 10.1007/s00778-013-0319-9

C. Monash, Cloudera presents the mapreduce bull case, 2009.

H. Han, Y. C. Lee, S. Choi, H. Y. Yeom, and A. Y. Zomaya, Cloud-aware processing of mapreduce-based olap applications, Proceedings of the Eleventh Australasian Symposium on Parallel and Distributed Computing, pp.31-38, 2013.

H. Yang, A. Dasdan, R. Hsiao, and D. S. Parker, Map-reduce-merge, Proceedings of the 2007 ACM SIGMOD international conference on Management of data , SIGMOD '07, p.7, 2007.
DOI : 10.1145/1247480.1247602

W. H. Inmon, The data warehouse and data mining, Communications of the ACM, vol.39, issue.11, pp.49-50, 1996.
DOI : 10.1145/240455.240470

J. Dean and S. Ghemawat, MapReduce, USENIX Symposium on Operating Systems Design and Implementation (OSDI), 2004.
DOI : 10.1145/1327452.1327492

R. Pike, S. Dorward, R. Griesemer, and S. Quinlan, Interpreting the data: Parallel analysis with sawzall. Scientific Programming -Dynamic Grids and Worldwide Computing, pp.277-298, 2005.

T. White, Hadoop: The Definitive Guide, 2009.

J. Liu, E. Pacitti, P. Valduriez, and M. Mattoso, A Survey of Data-Intensive Scientific Workflow Management, Journal of Grid Computing, vol.1, issue.Webserver-Issue, 2015.
DOI : 10.1007/s10723-015-9329-8
URL : https://hal.archives-ouvertes.fr/lirmm-01144760

J. Liu, V. Silva, E. Pacitti, P. Valduriez, and M. Mattoso, Scientific workflow partitioning in multi-site clouds, Euro-Par 2014: Parallel Processing Workshops, pp.1-12, 2014.
URL : https://hal.archives-ouvertes.fr/lirmm-01073613

B. Nicolae, G. Antoniu, L. Bougé, D. Moise, and A. Carpen-amarie, BlobSeer: Next-generation data management for large scale infrastructures, Journal of Parallel and Distributed Computing, vol.71, issue.2, pp.169-184, 2011.
DOI : 10.1016/j.jpdc.2010.08.004
URL : https://hal.archives-ouvertes.fr/inria-00511414

E. Ogasawara, D. Oliveira, P. Valduriez, J. Dias, F. Porto et al., An algebraic approach for data-centric scientific workflows, Proceedings of the VLDB Endowment (PVLDB), pp.1328-1339, 2011.
URL : https://hal.archives-ouvertes.fr/hal-00640431

D. Oliveira, K. A. Ocaña, E. Ogasawara, J. Dias, J. Gonçalves et al., Performance evaluation of parallel strategies in public clouds: A study with phylogenomic workflows, Future Generation Computer Systems, vol.29, issue.7, pp.291816-1825, 2013.
DOI : 10.1016/j.future.2012.12.019

M. T. Ozsu and P. Valduriez, Principles of Distributed Database Systems, 2011.
URL : https://hal.archives-ouvertes.fr/hal-00483354

E. Pacitti, R. Akbarinia, and M. E. Dick, P2P Techniques for Decentralized Applications, 2012. expression data. Fundamenta Informaticae, pp.543-559, 2007.
DOI : 10.2200/S00414ED1V01Y201204DTM025
URL : https://hal.archives-ouvertes.fr/lirmm-00748635

H. Blockeel, T. Calders, E. Fromont, B. Goethals, A. Prado et al., A Practical Comparative Study Of Data Mining Query Languages, Inductive Databases and Constraint-Based Data Mining, pp.59-77, 2010.
DOI : 10.1007/978-1-4419-7738-0_3
URL : https://hal.archives-ouvertes.fr/hal-00531167

H. Blockeel, T. Calders, ´. E. Fromont, B. Goethals, A. Prado et al., An inductive database system based on virtual mining views, Data Mining and Knowledge Discovery, vol.2, issue.2
DOI : 10.1007/s10618-011-0229-7
URL : https://hal.archives-ouvertes.fr/hal-00599315

P. Bohannon, W. Fan, F. Geerts, X. Jia, and A. Kementsietsidis, Conditional Functional Dependencies for Data Cleaning, 2007 IEEE 23rd International Conference on Data Engineering, pp.746-755, 2007.
DOI : 10.1109/ICDE.2007.367920
URL : http://citeseerx.ist.psu.edu/viewdoc/summary?doi=10.1.1.259.8695

B. Chardin, E. Coquery, B. Gouriou, M. Pailloux, and J. Petit, Query Rewriting for Rule Mining in Databases, Languages for Data Mining and Machine Learning, in conjunction with ECML/PKDD, pp.35-49, 2013.
URL : https://hal.archives-ouvertes.fr/hal-01339257

L. Fang and K. Lefevre, Splash, Proceedings of the 13th International Conference on Extending Database Technology, EDBT '10, pp.275-286, 2010.
DOI : 10.1145/1739041.1739076

B. Ganter and R. Wille, Formal Concept Analysis, 1999.

T. Guns, S. Nijssen, and L. D. Raedt, Itemset mining: A constraint programming perspective, Artificial Intelligence, vol.175, issue.12-13, pp.12-131951, 2011.
DOI : 10.1016/j.artint.2011.05.002

N. Koudas, A. Saha, D. Srivastava, and S. Venkatasubramanian, Metric Functional Dependencies, 2009 IEEE 25th International Conference on Data Engineering, pp.1275-1278, 2009.
DOI : 10.1109/ICDE.2009.219
URL : http://citeseerx.ist.psu.edu/viewdoc/summary?doi=10.1.1.184.1946

S. Lopes, J. Petit, and L. Lakhal, Efficient Discovery of Functional Dependencies and Armstrong Relations, Advances in Database Technology -EDBT 2000, 7th International Conference on Extending Database Technology Proceedings, pp.350-364, 2000.
DOI : 10.1007/3-540-46439-5_24
URL : https://hal.archives-ouvertes.fr/hal-00271567

K. Murakami and T. Uno, Efficient algorithms for dualizing large-scale hypergraphs, 1102.

A. Netz, S. Chaudhuri, J. Bernhardt, and U. M. Fayyad, Integration of data mining with database technology, Proceedings of the 26th International Conference on Very Large Data Bases, VLDB '00, pp.719-722, 2000.

C. Ordonez and S. K. Pitchaimalai, One-pass data mining algorithms in a DBMS with UDFs, Proceedings of the 2011 international conference on Management of data, SIGMOD '11, pp.1217-1220, 2011.
DOI : 10.1145/1989323.1989458

D. Ashbrook and T. Starner, Using GPS to learn significant locations and predict movement across multiple users, English. In: Personal and Ubiquitous Computing, pp.275-286, 2003.
DOI : 10.1007/s00779-003-0240-0

L. Bao and S. Intille, Activity Recognition from User-Annotated Acceleration Data, Lecture Notes in Computer Science, vol.3001, pp.1-17, 2004.
DOI : 10.1007/978-3-540-24646-6_1
URL : http://citeseerx.ist.psu.edu/viewdoc/summary?doi=10.1.1.68.5133

J. Biagioni, T. Gerlich, T. Merrifield, and J. Eriksson, EasyTracker, Proceedings of the 9th ACM Conference on Embedded Networked Sensor Systems, SenSys '11, pp.68-81, 2011.
DOI : 10.1145/2070942.2070950

H. H. Bui, S. Venkatesh, and G. West, Policy Recognition in the Abstract Hidden Markov Model, In: J. Artif. Int. Res, vol.17, issue.1, pp.451-499, 2002.

J. Chen and M. Bierlaire, Probabilistic Multimodal Map Matching With Rich Smartphone Data, Journal of Intelligent Transportation Systems: Technology, Planning and Operations, 2013.
DOI : 10.1145/1409635.1409677

. Ios-developer and . Library, CMMotionActivity Class Reference . 2013. url: https://developer.apple.com/ library, Reference.html, vol.16, 2014.

A. Doucet, N. De-freitas, K. Murphy, and S. Russell, Rao-blackwellised Particle Filtering for Dynamic Bayesian Networks, Proceedings of the Sixteenth Conference on Uncertainty in Artificial Intelligence. UAI'00, pp.176-183, 2000.

A. Doucet, N. Freitas, and N. G. English, An Introduction to Sequential Monte Carlo Methods, Statistics for Engineering and Information Science, pp.3-14, 2001.
DOI : 10.1007/978-1-4757-3437-9_1

G. Flötteröd and M. Bierlaire, Metropolis???Hastings sampling of paths, Transportation Research Part B: Methodological, vol.48, pp.53-66, 2013.
DOI : 10.1016/j.trb.2012.11.002

D. Fox, J. Hightower, L. Liao, D. Schulz, and G. Borriello, Bayesian filtering for location estimation, IEEE Pervasive Computing, vol.2, issue.3, pp.24-33, 2003.
DOI : 10.1109/MPRV.2003.1228524

E. Foxlin, Pedestrian Tracking with Shoe-Mounted Inertial Sensors, Computer Graphics and Applications, pp.38-46, 2005.
DOI : 10.1109/MCG.2005.140

S. Hemminki, P. Nurmi, and S. Tarkoma, Accelerometerbased Transportation Mode Detection on Smartphones, Proceedings of the 11th ACM Conference on Embedded Networked Sensor Systems. SenSys '13, pp.1-1314, 2013.

J. R. Kwapisz, G. M. Weiss, and S. A. Moore, Activity recognition using cell phone accelerometers, ACM SIGKDD Explorations Newsletter, vol.12, issue.2, pp.74-82, 2011.
DOI : 10.1145/1964897.1964918
URL : http://citeseerx.ist.psu.edu/viewdoc/summary?doi=10.1.1.188.3680

L. Liao, D. J. Patterson, D. Fox, and H. Kautz, Learning and inferring transportation routines, Artificial Intelligence, vol.171, issue.5-6, pp.311-331, 2007.
DOI : 10.1016/j.artint.2007.01.006
URL : http://doi.org/10.1016/j.artint.2007.01.006

Y. Lou, C. Zhang, Y. Zheng, X. Xie, W. Wang et al., Map-matching for low-sampling-rate GPS trajectories, Proceedings of the 17th ACM SIGSPATIAL International Conference on Advances in Geographic Information Systems, GIS '09, pp.352-361, 2009.
DOI : 10.1145/1653771.1653820

V. Manzoni, D. Maniloff, K. Kloeckl, and C. Ratti, Transportation mode identification and real-time CO2 emission estimation using smartphones, 2010.

U. Maurer, A. Smailagic, D. P. Siewiorek, and M. Deisher, Activity Recognition and Monitoring Using Multiple Sensors on Different Body Positions, International Workshop on Wearable and Implantable Body Sensor Networks (BSN'06), p.4, 2006.
DOI : 10.1109/BSN.2006.6
URL : http://citeseerx.ist.psu.edu/viewdoc/summary?doi=10.1.1.683.9829

K. P. Murphy, Dynamic bayesian networks: representation , inference and learning, 2002.

P. Newson and J. Krumm, Hidden Markov map matching through noise and sparseness, Proceedings of the 17th ACM SIGSPATIAL International Conference on Advances in Geographic Information Systems, GIS '09, pp.336-343, 2009.
DOI : 10.1145/1653771.1653818
URL : http://citeseerx.ist.psu.edu/viewdoc/summary?doi=10.1.1.187.5145

J. Parkka, M. Ermes, P. Korpipaa, J. Mantyjarvi, J. Peltola et al., Activity Classification Using Realistic Data From Wearable Sensors, IEEE Transactions on Information Technology in Biomedicine, vol.10, issue.1, pp.119-128, 2006.
DOI : 10.1109/TITB.2005.856863

M. A. Quddus, W. Y. Ochieng, and R. B. Noland, Current map-matching algorithms for transport applications: State-of-the art and future research directions, Transportation Research Part C: Emerging Technologies, vol.15, issue.5, pp.312-328, 2007.
DOI : 10.1016/j.trc.2007.05.002

N. Ravi, N. Dandekar, P. Mysore, and M. L. Littman, Activity recognition from accelerometer data, In: AAAI, vol.5, pp.1541-1546, 2005.

S. Reddy, M. Mun, J. Burke, D. Estrin, M. Hansen et al., Using mobile phones to determine transportation modes, ACM Transactions on Sensor Networks, vol.6, issue.2, p.13, 2010.
DOI : 10.1145/1689239.1689243

A. Thiagarajan, J. Biagioni, T. Gerlich, and J. Eriksson, Cooperative transit tracking using smart-phones, Proceedings of the 8th ACM Conference on Embedded Networked Sensor Systems, SenSys '10, pp.85-98, 2010.
DOI : 10.1145/1869983.1869993

A. Thiagarajan, L. Ravindranath, K. Lacurts, S. Madden, H. Balakrishnan et al., VTrack, Proceedings of the 7th ACM Conference on Embedded Networked Sensor Systems, SenSys '09, pp.85-98, 2009.
DOI : 10.1145/1644038.1644048

S. Wang, C. Chen, and J. Ma, Accelerometer Based Transportation Mode Recognition on Mobile Phones, 2010 Asia-Pacific Conference on Wearable Computing Systems, pp.44-46, 2010.
DOI : 10.1109/APWCS.2010.18

Y. Zheng, Y. Chen, Q. Li, X. Xie, and W. Ma, Understanding transportation modes based on GPS data for web applications, ACM Transactions on the Web, vol.4, issue.1, p.1, 2010.
DOI : 10.1145/1658373.1658374

D. J. Abadi, A. Marcus, S. R. Madden, and K. Hollenbach, Scalable semantic web data management using vertical partitioning, Proceedings of the 33rd international conference on Very large data bases, pp.411-422, 2007.

D. J. Abadi, A. Marcus, S. R. Madden, and K. Hollenbach, SW-Store: a vertically partitioned DBMS for Semantic Web data management, The VLDB Journal, vol.17, issue.2, pp.385-406, 2009.
DOI : 10.1007/s00778-008-0125-y

T. Ball, The Concept of Dynamic Analysis, Software Engineering ESEC/FSE '99, pp.216-234, 1999.
DOI : 10.1007/3-540-48166-4_14

T. Ball and J. R. Larus, Optimally profiling and tracing programs, ACM Transactions on Programming Languages and Systems, vol.16, issue.4, pp.1319-1360, 1994.
DOI : 10.1145/183432.183527
URL : http://citeseerx.ist.psu.edu/viewdoc/summary?doi=10.1.1.111.6293

R. Cyganiak, A relational algebra for sparql. Digital Media Systems Laboratory HP Laboratories Bristol. HPL-2005-170, p.35, 2005.

C. David, C. Olivier, and B. Guillaume, A survey of rdf storage approaches, ARIMA Journal, vol.15, pp.11-35, 2012.

L. C. Fopa, J. Fabrice, A. Termier, T. Maurice, and I. Oleg, Benchmarking of triple stores scalability for mpsoc trace analysis, 2nd International Workshop on Benchmarking RDF Systems, 2014.
URL : https://hal.archives-ouvertes.fr/hal-01411357

A. Hamou-lhadj and T. C. Lethbridge, A survey of trace exploration tools and techniques, Proceedings of the 2004 conference of the Centre for Advanced Studies on Collaborative research, pp.42-55, 2004.

S. Harris and N. Shadbolt, SPARQL Query Processing with Conventional Relational Database Systems, Web Information Systems Engineering?WISE, 2005.
DOI : 10.1007/11581116_25
URL : http://citeseerx.ist.psu.edu/viewdoc/summary?doi=10.1.1.100.4934

A. Jena, A free and open source Java framework for building Semantic Web and Linked Data applications [Online, 2011.

C. Kamdem-kengne, L. C. Fopa, A. Termier, N. Ibrahim, M. Rousset et al., Efficiently rewriting large multimedia application execution traces with few event sequences, Proceedings of the 19th ACM SIGKDD international conference on Knowledge discovery and data mining, KDD '13, pp.1348-1356, 2013.
DOI : 10.1145/2487575.2488211

. Monetdb, Monetdb colums-store pioneers. https://www.monetdb.org, 2008.

M. Stonebraker, D. J. Abadi, A. Batkin, X. Chen, M. Cherniack et al., C-store : a column-oriented dbms, Proceedings of the 31st international conference on Very large data bases, pp.553-564, 2005.

M. Jelasity and O. Babaoglu, T-Man: Gossip-Based Overlay Topology Management, ESOA, pp.1-15, 2005.
DOI : 10.1007/978-3-540-39671-0_5
URL : http://citeseerx.ist.psu.edu/viewdoc/summary?doi=10.1.1.62.9444

A. Joly, H. Goëau, P. Bonnet, B. Vera, J. Barbe et al., Interactive plant identification based on social image data, Ecological Informatics, 2013.
DOI : 10.1016/j.ecoinf.2013.07.006
URL : https://hal.archives-ouvertes.fr/hal-00908872

W. Kowalczyk, M. Jelasity, and A. Eiben, Towards data mining in large and fully distributed peer-to-peer overlay networks, BNAIC, pp.203-210, 2003.

G. Salton, Automatic Information Organization and Retrieval, 1968.

M. Servajean, E. Pacitti, S. Amer-yahia, and P. Neveu, Profile diversity in search and recommendation, Proceedings of the 22nd International Conference on World Wide Web, WWW '13 Companion, pp.973-980, 2013.
DOI : 10.1145/2487788.2488094
URL : https://hal.archives-ouvertes.fr/lirmm-00806676

S. Ahmad, A. Battle, Z. Malkani, and S. Kamvar, The jabberwocky programming environment for structured social computing, Proceedings of the 24th annual ACM symposium on User interface software and technology, UIST '11, pp.53-64, 2011.
DOI : 10.1145/2047196.2047203

W. Daniel, C. Barowy, E. D. Curtsinger, A. Berger, and . Mcgregor, Automan: a platform for integrating human-based and digital computation, SIGPLAN Not, vol.47, issue.10, pp.639-654, 2012.

A. Bozzon, M. Brambilla, S. Ceri, and A. Mauri, Reactive crowdsourcing, Proceedings of the 22nd international conference on World Wide Web, WWW '13, pp.153-164, 2013.
DOI : 10.1145/2488388.2488403
URL : http://citeseerx.ist.psu.edu/viewdoc/summary?doi=10.1.1.594.6198

A. Bozzon, M. Brambilla, S. Ceri, M. Silvestri, and G. Vesci, Choosing the right crowd, Proceedings of the 16th International Conference on Extending Database Technology, EDBT '13, pp.637-648, 2013.
DOI : 10.1145/2452376.2452451

M. J. Franklin, D. Kossmann, T. Kraska, S. Ramesh, and R. Xin, CrowdDB, Proceedings of the 2011 international conference on Management of data, SIGMOD '11, pp.61-72, 2011.
DOI : 10.1145/1989323.1989331

A. Marcus, E. Wu, D. Karger, S. Madden, and R. Miller, Human-powered sorts and joins, Proceedings of the VLDB Endowment, vol.5, issue.1, pp.13-24, 2011.
DOI : 10.14778/2047485.2047487
URL : http://arxiv.org/abs/1109.6881

. Cylog, crowd4u: a declarative platform for complex data-centric crowdsourcing, Proc. VLDB Endow, pp.1918-1921, 2012.

H. Park, R. Pang, A. Parameswaran, H. Garcia-molina, N. Polyzotis et al., An overview of the deco system, ACM SIGMOD Record, vol.41, issue.4, pp.22-27, 2013.
DOI : 10.1145/2430456.2430462