, membre de la commission ingénieur de INRIA Nancy Grand Est. -2009?présent membre du comité d'organisation du séminaire IPAC « Image, 2008.

L. Membre-de-la-commission-bureau-du-laboratoire, Objectif : repenser l'attribution des bureaux aux différentes équipes de recherche. -2012?présent membre de la commission de recrutement ATER et DCCE de l'UFR MI, en lien avec le laboratoire LORIA en vue d'une harmonisation des recrutements entre composantes, 2014 membre nommé du groupe de travail du LORIA sur les Masters en rapport avec l'informatique en Lorraine. Groupe formé à l'initiative du Laboratoire LORIA

, Animation et administration de l'enseignement

, Responsabilité d'un diplôme de Licence Depuis 2012, je suis responsable de la Licence MIASHS -Mathématiques et Informatique Appliquées aux Sciences Humaines et Sociales Je suis par ailleurs présidente de jury et responsable du processus de recrutement en Licence (recrutement sur dossier et entretien oral pour les candidatures en L2 et L3) Je suis également en charge de l'étude des dossiers Campus France, Direction de formations 2012?présent

. Je-suis-porteur-de-la-maquette, Université en Octobre 2016) : j'ai animé les réunions de réflexion autour des évolutions pédagogiques, définition des nouveaux contenus, rédéfinition du socle commun aux parcours. J'ai également mis en place des accords privilégiés avec les porteurs d'autres licences, 2018.

, A ce titre, j'assure le recrutement des enseignants, définis et gère les emplois du temps. Par ailleurs j'accompagne et conseille les étudiants au jour le jour (administratif, pédagogique, Je suis par ailleurs directrice des études du parcours Sciences Cognitives

, Information des Organisations, géré par l'UFR et financé par la région Lorraine Cette formation qualifiante est destinée à un public en recherche d'emploi. La formation a lieu sur sept mois, chaque année, et se déroule à temps plein Mes responsabilités ont concerné la sélection des candidats (dossiers + entretiens oraux), le recrutement des enseignants, la gestion de l'emploi du temps, le suivi du déroulement de la formation, du stage et le lien avec le service de formation continue de l'Université. 5.6.2 Diffusion Je suis très active dans la promotion de l'offre de formation des diplômes de l'UFR MI, pour lesquels j'effectue chaque année un grand nombre d'actions de communication auprès des enseignants, conseillers d'orientation, lycéens et des étudiants de BTS/DUT. Je co-organise chaque année le forum des Sciences Cognitives de Nancy. Ce forum, d'une durée d'une journée, a pour objectif de faire découvrir aux étudiants de l'UFR MI, Responsabilité du cycle de formation continue ADSIO J'ai eu la responsabilité du cycle de formation continue ADSIO Analyste Développeur en Systèmes d aux étudiants de toutes filières de l'Université, aux lycéens mais aussi au grand public, les Sciences Cognitives sous toutes leurs formes. Tout au long de la journée, des exposés scientifiques et professionnels, ainsi que des démonstrations sont faites par des industriels et des chercheurs. En 2013, j'ai co-organisé (nous étions 2 organisateurs) les Journées Nationales MIAGE à Nancy qui ont rassemblé plus de 500 personnes : des représentants des équipes pédagogiques et des étudiants des 20 MIAGE de France, pp.16-18, 2004.

. Abboud, CCPM: A Scalable and Noise-Resistant Closed Contiguous Sequential Patterns Mining Algorithm, 13th International Conference on Machine Learning and Data Mining MLDM 2017, p.15, 2017.
DOI : 10.1016/j.knosys.2015.06.014

URL : https://hal.archives-ouvertes.fr/hal-01569008

. Abboud, Predict the emergence ? application to competencies in job offers, International Conference on Tools with Artificial Intelligence (ICTAI), 2015.
URL : https://hal.archives-ouvertes.fr/hal-01254179

. Achar, Discovering injective episodes with general partial orders, Data Mining and Knowledge Discovery, vol.22, issue.4, pp.67-108, 2012.
DOI : 10.1162/neco.2009.12-08-928

T. Adomavicius, G. Adomavicius, and A. Tuzhilin, Toward the next generation of recommender systems: a survey of the state-of-the-art and possible extensions, IEEE Transactions on Knowledge and Data Engineering, vol.17, issue.6, pp.17734-749, 2005.
DOI : 10.1109/TKDE.2005.99

Z. Adomavicius, G. Adomavicius, and J. Zhang, Impact of data characteristics on recommender systems performance, ACM Transactions on Management Information Systems, vol.3, issue.1, pp.1-317, 2012.
DOI : 10.1145/2151163.2151166

Y. Aggarwal, C. Aggarwal, and S. Yu, An effective and efficient algorithm for high-dimensional outlier detection, The VLDB Journal, vol.15, issue.2, pp.211-221, 2005.
DOI : 10.1007/s00778-004-0125-5

. Agrawal, Mining association rules between sets of items in large databases, ACM SIGMOD, pp.207-216, 1993.

S. Agrawal, R. Agrawal, and R. Srikant, Mining sequential patterns, Proceedings of the Eleventh International Conference on Data Engineering, pp.3-14, 1995.
DOI : 10.1109/ICDE.1995.380415

H. J. Ahn, A new similarity measure for collaborative filtering to alleviate the new user cold-starting problem, Information Sciences, vol.178, issue.1, pp.37-51, 2008.
DOI : 10.1016/j.ins.2007.07.024

A. , What about interpreting features in matrix factorization-based recommender systems as users ?, Workshop on Social Personalization at ACM HT conference, 2014.

A. , Identifying Representative Users in Matrix Factorization-based Recommender Systems : Application to Solving the Content-less New Item Cold-start Problem, Journal of Intelligent Information Systems, vol.48, issue.2, pp.365-397, 2017.

A. , Automatic formation of sets of contrasting rules to identify trigger factors, ECAI ? European Conference on Artificial Intelligence, 2016.

A. , Sets of contrasting rules : a supervised descriptive rule induction pattern for identification of trigger factors, Proceedings of the annual IEEE International Conference on Tools with Artificial Intelligence (ICTAI), 2016.

A. , Contrast classification rules for mining local differences in medical data, 9th IEEE International Conference on Intelligent Data Acquisition and Advanced Computing Systems : Technology and Applications (IDAACS'17), 2017.

. Bobadilla, A collaborative filtering approach to mitigate the new user cold start problem, Knowledge-Based Systems, vol.26, pp.225-238, 2012.
DOI : 10.1016/j.knosys.2011.07.021

. Bobadilla, Recommender systems survey. Knowledge-Based Systems, pp.109-132, 2013.

. Bonnin, Collaborative filtering inspired from language modeling, 2008 First International Conference on the Applications of Digital Information and Web Technologies (ICADIWT), 2008.
DOI : 10.1109/ICADIWT.2008.4664343

URL : https://hal.archives-ouvertes.fr/inria-00327070

. Bonnin, Using Skipping for Sequence-Based Collaborative Filtering, 2008 IEEE/WIC/ACM International Conference on Web Intelligence and Intelligent Agent Technology, pp.775-779, 2008.
DOI : 10.1109/WIIAT.2008.280

URL : https://hal.archives-ouvertes.fr/inria-00332238

. Bonnin, A low-order markov model integrating long-distance histories for collaborative recommender systems, Proceedingsc of the 13th international conference on Intelligent user interfaces, IUI '09, pp.57-66, 2009.
DOI : 10.1145/1502650.1502662

URL : https://hal.archives-ouvertes.fr/inria-00341537

. Bonnin, Renforcement des modèles probabilistes en utilisant l'Information Mutuelle pour des Recommandations contextualisées, 7e colloque du chapitre français de l'ISKO -Intelligence collective et organisation des connaissances, 2009.

. Bonnin, Detecting Parallel Browsing to Improve Web Predictive Modeling, International Conference on Knowledge Discovery and Information Retrieval -KDIR 2010, pp.504-509, 2010.
URL : https://hal.archives-ouvertes.fr/inria-00505197

. Bonnin, Towards tabbing aware recommendations, Proceedings of the First International Conference on Intelligent Interactive Technologies and Multimedia, IITM '10, 2010.
DOI : 10.1145/1963564.1963619

URL : https://hal.archives-ouvertes.fr/inria-00545454

. Bonnin, Web Intelligence and Intelligent Agents, chapter Skipping-Based Collaborative Recommendations Inspired from Statistical Language Modeling, pp.263-288, 2010.

. Bonnin, Handling Tabbing and Backward References for Predictive Web Usage Mining, Proc. of the International Joint Conference on Knowledge Discovery and Information Retrieval, 2011.

. Bonnin, Taking into account tabbed browsing in predictive web usage mining, Proc. of the First International Conference on Social Eco-Informatics, 2011.

. Bonnin, Exploitation du skipping pour la mod??lisation pr??dictive des usages du web. Vers une meilleure prise en compte du bruit, Revue des Sciences et Technologies de l'Information -Série RIA : Revue d'Intelligence Artificielle, pp.609-642, 2012.
DOI : 10.3166/ria.26.609-642

B. Boumaza, A. Boumaza, and A. Brun, From neighbors to global neighbors in collaborative filtering, Proceedings of the fourteenth international conference on Genetic and evolutionary computation conference, GECCO '12, pp.345-352, 2012.
DOI : 10.1145/2330163.2330214

URL : https://hal.archives-ouvertes.fr/hal-00778495

B. Boumaza, A. Boumaza, and A. Brun, Stochastic search for global neighbors selection in collaborative filtering, Proceedings of the 27th Annual ACM Symposium on Applied Computing, SAC '12, 2012.
DOI : 10.1145/2245276.2245322

URL : https://hal.archives-ouvertes.fr/hal-00778497

B. Boyer, A. Boyer, and A. Brun, Natural Language Processing for Usage Based Indexing of Web Resources, 29th European Conference on Information Retrieval, pp.517-524, 2007.
DOI : 10.1007/978-3-540-71496-5_46

URL : https://hal.archives-ouvertes.fr/inria-00172231

B. Boyer, A. Boyer, and A. Brun, Towards a statistical grammar of usage for document retrieval in digital libraries, 2007 9th International Symposium on Signal Processing and Its Applications, 2007.
DOI : 10.1109/ISSPA.2007.4555494

URL : https://hal.archives-ouvertes.fr/inria-00119476

. Boyer, Human Computer Collaboration to Improve Annotations in Semantic Wikis, 6th International Conference on Web Information Systems and Technologies -WEBIST 2010, pp.89-94, 2010.
URL : https://hal.archives-ouvertes.fr/inria-00378416

. Brown, A statistical approach to machine translation, Computational Linguistics, vol.16, issue.2, pp.79-85, 1990.

A. Brun, Identification de thèmes pour la modélisation statistique du langage, 1999.

A. Brun, Détection de thèmes et adaptation des modèles de langage pour la reconnaissance automatique de la parole, 2003.

. Brun, Can Latent Features Be Interpreted as Users in Matrix Factorization-Based Recommender Systems?, 2014 IEEE/WIC/ACM International Joint Conferences on Web Intelligence (WI) and Intelligent Agent Technologies (IAT), 2014.
DOI : 10.1109/WI-IAT.2014.102

URL : https://hal.archives-ouvertes.fr/hal-01108807

. Brun, History Dependent Recommender Systems Based on Partial Matching Adaptation and Personalization -UMAP, First and Seventeenth International Conference on User Modeling, pp.343-348, 2009.
DOI : 10.1007/978-3-642-02247-0_34

URL : http://hal.archives-ouvertes.fr/docs/00/43/05/92/PDF/umap09.pdf

. Brun, A. Boyer-]-brun, and A. Boyer, Usage based Indexing of Web Resources with Natural Language Processing, 3rd International Conference on Web Information Systems and Techonologies, 2007.
URL : https://hal.archives-ouvertes.fr/inria-00172234

A. Brun and A. Boyer, Towards Privacy Compliant and Anytime Recommender Systems, 10th International Conference on Electronic Commerce and Web Technologies -EC-Web 09, pp.276-287, 2009.
DOI : 10.1016/j.knosys.2006.04.001

URL : https://hal.archives-ouvertes.fr/inria-00430595

. Brun, . Boyer, A. Brun, and A. Boyer, Are Recommender Systems Real-Time in Mobile Environment ? Towards Instantaneous Recommenders, 6th International Conference on Web Information Systems and Technologies, pp.101-106, 2010.
URL : https://hal.archives-ouvertes.fr/inria-00523489

. Brun, . Boyer, A. Brun, and A. Boyer, Du e-commerce au m-commerce : vers une Recommandation Incrémentale, Proc. of the 7th COnférence en Recherche d'Information et Applications (CORIA), 2010.

. Brun, . Boyer, A. Brun, and A. Boyer, Linking Collaborative Filtering and Social Networks: Who Are My Mentors?, 2010 International Conference on Advances in Social Networks Analysis and Mining, 2010.
DOI : 10.1109/ASONAM.2010.41

URL : https://hal.archives-ouvertes.fr/inria-00523491

. Brun, A. Boyer-]-brun, and A. Boyer, Inspiration des sondages d'opinion pour réduire la latence en filtrage collaboratif, COnférence en Recherche d'Information et Applications -CORIA 2011, pp.49-56, 2011.

. Brun, . Boyer, A. Brun, and A. Boyer, D??tection de communaut??s d???int??r??t et recommandation sociale par leaders, Ingéniérie des Systèmes d'Information (ISI) -Numéro Spécial "Impact des réseaux sociaux et du Web 2, 2012.
DOI : 10.3166/isi.17.6.91-113

. Brun, Compass to Locate the User Model I Need: Building the Bridge between Researchers and Practitioners in User Modeling, User Modeling, Adaptation and Personalization -UMAP 2010, pp.303-314, 2010.
DOI : 10.1007/978-3-642-13470-8_28

URL : https://hal.archives-ouvertes.fr/inria-00523498

. Brun, A Positively Directed Mutual Information Measure for Collaborative Filtering, 2nd Conférence Internationale Systèmes d'Information et Intelligence Economique, pp.943-958, 2009.
URL : https://hal.archives-ouvertes.fr/inria-00430638

. Brun, From Community Detection to Mentor Selection in Rating-Free Collaborative Filtering, Advances in Multimedia Journal, pp.1-19, 2011.
DOI : 10.1023/A:1020443909834

URL : https://hal.archives-ouvertes.fr/inria-00580116

. Brun, Social Network Mining, Analysis and Research Trends : Techniques and Applications, chapter Social Recommendations : Mentor and Leader Detection to Alleviate the Cold-Start Problem in Collaborative Filtering, 2011.

. Brun, Ants, Appalachian Heritage, vol.30, issue.3, 2004.
DOI : 10.1353/aph.2002.0082

URL : https://hal.archives-ouvertes.fr/inria-00107762

. Brun, Analyse de besoins pour un service en ligne, Environnements Informatiques pour l'Apprentissage Humain (EIAH), 2015.
URL : https://hal.archives-ouvertes.fr/hal-01254183

. Brun, Needs analysis for an online learning service, IFIP TC3 Working Conference, 2015.
URL : https://hal.archives-ouvertes.fr/hal-01254182

. Brun, From "I Like" to "I Prefer" in Collaborative Filtering, 2010 22nd IEEE International Conference on Tools with Artificial Intelligence, pp.365-367, 2010.
DOI : 10.1109/ICTAI.2010.129

URL : https://hal.archives-ouvertes.fr/inria-00535566

. Brun, Towards Preference Relations in Recommender Systems, Workshop on Preference Learning (PL2010) in ECML-PKDD, 2010.
URL : https://hal.archives-ouvertes.fr/inria-00523496

. Brun, Vers l'utilisation de relations de préférence pour le filtrage collaboratif, 17eme congrès francophone Reconnaissance des Formes et Intelligence Artificielle -RFIA 2010, 2010.

. Brun, Exploration et utilisation d'informations distantes dans les modèles statistiques de langage, Traitement Automatique des Langues Naturelles (TALN2006), pp.425-434, 2006.

. Brun, Improving language models by using distant information, 2007 9th International Symposium on Signal Processing and Its Applications, 2007.
DOI : 10.1109/ISSPA.2007.4555480

URL : https://hal.archives-ouvertes.fr/inria-00187084

. Brun, Discarding Impossible Events from Statistical Language Models, International Conference on Spoken Language Processing (ICSLP2000), pp.981-984, 2000.
URL : https://hal.archives-ouvertes.fr/inria-00099040

. Brun, Improving Statistical Language Models by Removing Impossible Events, Proceedings of the International Workshop " Speech and Computer " -SPECOM 2001, 2001.
URL : https://hal.archives-ouvertes.fr/inria-00100651

. Brun, Improving Statistical Language Models by Removing Impossible Events, International Workshop "Speech and Computer, 2001.
URL : https://hal.archives-ouvertes.fr/inria-00100651

. Brun, Raising up Annotations In Pedagogical Resources by Human-Computer Collaboration, European Distance and E-learning Network, 2010.
URL : https://hal.archives-ouvertes.fr/inria-00597285

. Brun, Raising up Annotations In Pedagogical Resources by Human-Computer Collaboration, Research Workshop European Distance and E-learning Network, 2010.
URL : https://hal.archives-ouvertes.fr/inria-00597285

S. Brun, A. Brun, and K. Smaïli, Fiabilité de la référence humaine dans la détection de thème, Traitement Automatique des Langues Naturelles, 2004.

. Brun, Topic Identification Challenge Based on Short Word History, Traitement automatique des Langues Naturelles (TALN2000), pp.383-392, 2000.
URL : https://hal.archives-ouvertes.fr/inria-00099124

. Brun, Contribution to Topic Identification by Using Word Similarity, International Conference on Spoken Language Processing (ICSLP2002), pp.1965-1968, 2002.
URL : https://hal.archives-ouvertes.fr/inria-00100947

. Brun, WSIM : une méthode de détection de thème fondée sur la similarité entre mots, Traitement Automatique des Langues Naturelles (TALN2002), pp.145-154, 2002.

. Brun, Nouvelle approche de la sélection de vocabulaire pour la détection de thème, Traitement Automatique des Langues Naturelles (TALN2003), pp.45-54, 2003.

. Brun, Experiment analysis in newspaper topic detection, Proceedings Seventh International Symposium on String Processing and Information Retrieval. SPIRE 2000, pp.55-64, 2000.
DOI : 10.1109/SPIRE.2000.878180

URL : https://hal.archives-ouvertes.fr/inria-00099394

. Buffet, . Sigaud, O. Buffet, and O. Sigaud, Processus décisionnels de Markov en intelligence artificielle. IC2 -informatique et systèmes d'information, 2008.

S. Bull and J. Kay, Open learner models Advances in intelligent tutoring systems, pp.301-322, 2010.

. Cai, Learning to explore and exploit in pomdps, Advances in Neural Information Processing Systems, pp.198-206, 2009.

. Campos, Time-aware recommender systems: a comprehensive survey and analysis of existing evaluation protocols, User Modeling and User-Adapted Interaction, vol.107, issue.10, pp.67-119, 2014.
DOI : 10.1073/pnas.1000488107

. Candillier, Comparing State-of-the-Art Collaborative Filtering Systems, Proc. of 5th International Conference on Machine Learning and Data Mining in Pattern Recognition, MLDM'07, pp.548-562, 2007.
DOI : 10.1007/978-3-540-73499-4_41

. Castagnos, Probabilistic Association Rules for Item-Based Recommender Systems, 4th European Starting AI Researcher Symposium (STAIRS 2008), in conjunction with the 18th European Conference on Artificial Intelligence, pp.36-46, 2008.
URL : https://hal.archives-ouvertes.fr/inria-00329559

. Castagnos, Probabilistic Reinforcement Rules for Item-Based Recommender Systems, ECCAI, editor, 18th European Conference on Artificial Intelligence, pp.823-824, 2008.
URL : https://hal.archives-ouvertes.fr/inria-00329560

. Castagnos, Utilité et perception de la diversité dans les systèmes de recommandation, Proceedings of the 10th COnférence en Recherche d'Information et Applications, pp.237-252, 2013.

. Castagnos, When diversity is needed... but not expected !, Proceedings of the Third International Conference on Advances in Information Mining and Management IMMM 2013, pp.44-50, 2013.
URL : https://hal.archives-ouvertes.fr/hal-00931805

. Castagnos, La diversité : entre besoin et méfiance dans les systèmes de recommandation, Journal Interaction Intelligence Information, 2014.

. Castells, Novelty and Diversity in Recommender Systems, Recommender Systems Handbook, pp.881-918, 2015.
DOI : 10.1007/978-1-4899-7637-6_26

. Cena, How scales influence user rating behaviour in recommender systems, Behaviour & Information Technology, vol.2009, issue.1, pp.1-20, 2017.
DOI : 10.1093/poq/nfu062

C. , An effective recommendation method for cold start new users using trust and distrust networks, Information Sciences, vol.224, pp.19-36, 2013.

C. , G. Chen, S. Goodman, and J. , An empirical study of smoothing techniques for language modeling, 1998.

C. , G. Chen, S. F. Goodman, and J. , An empirical study of smoothing techniques for language modeling, Proceedings of the Thirty-Fourth Annual Meeting of the Association for Computational Linguistics, pp.310-318, 1996.

. Chertov, Comparative analysis of neighborhood-based approach and matrix factorization in recommender systems, Eastern- European Journal of Enterprise Technologies, vol.3, 2015.

. Chimphlee, Using Association Rules and Markov Model for Predit Next Access on Web Usage Mining, pp.371-376, 2006.
DOI : 10.1007/1-4020-5263-4_58

N. Chomsky, Three models for the description of language, IEEE Transactions on Information Theory, vol.2, issue.3, pp.113-124, 1956.
DOI : 10.1109/TIT.1956.1056813

R. Clarkson, P. R. Clarkson, and A. J. Robinson, Language model adaptation using mixtures and an exponentially decaying cache, 1997 IEEE International Conference on Acoustics, Speech, and Signal Processing, 1997.
DOI : 10.1109/ICASSP.1997.596049

. Claypool, Combining content-based and collaborative filters in an online newspaper, Proceedings of the SIGIR Workshop on Recommender Systems : Algorithms and Evaluation, 1999.

. Cleger, Learning from explanations in recommender systems, Information Sciences, vol.287, pp.90-108, 2014.
DOI : 10.1016/j.ins.2014.07.031

. Cooley, Web mining: information and pattern discovery on the World Wide Web, Proceedings Ninth IEEE International Conference on Tools with Artificial Intelligence, 1997.
DOI : 10.1109/TAI.1997.632303

. Cuong, A clustering approach for collaborative filtering recommendation using social network analysis, Journal of Universal Computer Science, vol.17, pp.583-604, 2011.

B. Daniel, Big Data and analytics in higher education: Opportunities and challenges, British Journal of Educational Technology, vol.15, issue.3, pp.904-920, 2015.
DOI : 10.5120/11648-7142

B. K. Daniel, Big Data in Higher Education: The Big Picture, Big Data and Learning Analytics in Higher Education, pp.19-28, 2017.
DOI : 10.5120/11648-7142

[. Bra, Web Dynamics, Adaptive to Change in Content, Size, Topology and Use, chapter Adaptive Web-based Educational Hypermedia, 2004.

C. De, Combining content-based and collaborative recommendations : A hybrid approach based on bayesian networks, International Journal of Approximate Reasoning, issue.7, pp.51785-799, 2010.

R. Domingos, P. Domingos, and M. Richardson, Mining the network value of customers, Proceedings of the seventh ACM SIGKDD international conference on Knowledge discovery and data mining , KDD '01, pp.57-66, 2001.
DOI : 10.1145/502512.502525

. Dujardin, ?-min : A compact approximate solver for finite-horizon pomdps, IJCAI, pp.2582-2588, 2015.

D. , A learning design recommandation system based on markov decision processes, 17th ACM SIGKDD conference on knowledge discovery and data mining, 2011.

E. Duval, Attention please!, Proceedings of the 1st International Conference on Learning Analytics and Knowledge, LAK '11, pp.9-17, 2011.
DOI : 10.1145/2090116.2090118

. Dwivedi, . Bharadwaj, P. Dwivedi, and K. K. Bharadwaj, e-Learning recommender system for a group of learners based on the unified learner profile approach, Expert Systems, vol.16, issue.1, pp.264-276, 2015.
DOI : 10.1007/s11257-006-9005-6

. Emami, Using a connectionist model in a syntactical based language model, 2003 IEEE International Conference on Acoustics, Speech, and Signal Processing, 2003. Proceedings. (ICASSP '03)., pp.372-375, 2003.
DOI : 10.1109/ICASSP.2003.1198795

. Esslimani, Behavioral similarities for collaborative recommendations, Journal of Digital Information Management, vol.6, issue.6, pp.442-448, 2008.
URL : https://hal.archives-ouvertes.fr/hal-00337730

. Esslimani, Enhancing collaborative filtering by frequent usage patterns, 2008 First International Conference on the Applications of Digital Information and Web Technologies (ICADIWT), pp.180-185, 2008.
DOI : 10.1109/ICADIWT.2008.4664341

URL : https://hal.archives-ouvertes.fr/hal-00337728

. Esslimani, A Collaborative Filtering Approach Combining Clustering and Navigational Based Correlations, 5th International Conference on Web Information Systems and Technologies -WEBIST 2009, pp.364-369, 2009.
URL : https://hal.archives-ouvertes.fr/inria-00395573

. Esslimani, From Social Networks to Behavioral Networks in Recommender Systems, 2009 International Conference on Advances in Social Network Analysis and Mining, pp.143-148, 2009.
DOI : 10.1109/ASONAM.2009.30

URL : https://hal.archives-ouvertes.fr/inria-00395679

. Esslimani, Detecting Leaders in Behavioral Networks, 2010 International Conference on Advances in Social Networks Analysis and Mining, pp.281-285, 2010.
DOI : 10.1109/ASONAM.2010.72

URL : https://hal.archives-ouvertes.fr/inria-00581415

. Esslimani, Detecting Leaders to Alleviate Latency in Recommender Systems, International Conference on Electronic Commerce and Web Technologies, pp.229-240, 2010.
DOI : 10.1007/978-3-642-15208-5_21

URL : https://hal.archives-ouvertes.fr/inria-00581416

. Esslimani, Densifying a behavioral recommender system by social networks link prediction methods, Social Network Analysis and Mining, vol.21, issue.1, pp.159-172, 2011.
DOI : 10.1093/bioinformatics/bti1012

URL : https://hal.archives-ouvertes.fr/inria-00430331

. Esslimani, The Influence of Technology on Social Network Analysis and Mining, Based Recommendations, pp.455-470, 2013.

L. Evans, J. Evans, and C. Lindner, Business analytics : The next frontier for decision sciences, 2012.

L. Facca, F. M. Facca, and P. L. Lanzi, Mining interesting knowledge from weblogs: a survey, Data & Knowledge Engineering, vol.53, issue.3, pp.225-241, 2005.
DOI : 10.1016/j.datak.2004.08.001

L. Fahed, Prédire et influencer l'apparition des événements dans une séquence complexe, 2016.

. Fahed, Episode Rules Mining Algorithm for Distant Event Prediction, Proceedings of the International Conference on Knowledge Discovery and Information Retrieval, 2014.
DOI : 10.5220/0005027600050013

URL : https://hal.archives-ouvertes.fr/hal-01108803

. Fahed, Extraction de règles d'épisodes minimales dans des séquences complexes, 14e Conférence Internationale Francophone sur l'Extraction et la Gestion de Connaissance, 2014.

. Fahed, Influencer Events in Episode Rules: A Way to Impact the Occurrence of Events, 19th International Conference on Knowledge-Based and Intelligent Information and Engineering Systems, 2015.
DOI : 10.1016/j.procs.2015.08.174

URL : https://hal.archives-ouvertes.fr/hal-01254175

. Fahed, Knowledge Discovery, Knowledge Engineering and Knowledge Management, chapter Efficient Discovery of Episode Rules With a Minimal Antecedent and a Distant Consequent, pp.3-18, 2015.

. Fahed, DEER : Distant and Essential Episode Rules for early prediction, Expert Systems with Applications, vol.93, pp.283-298, 2018.
DOI : 10.1016/j.eswa.2017.10.035

. Farabet, Learning Hierarchical Features for Scene Labeling, IEEE Transactions on Pattern Analysis and Machine Intelligence, vol.35, issue.8, p.35, 2013.
DOI : 10.1109/TPAMI.2012.231

URL : https://hal.archives-ouvertes.fr/hal-00742077

. Fayyad, From data mining to knowledge discovery in databases, 1996.

R. Ferguson, Learning analytics: drivers, developments and challenges, International Journal of Technology Enhanced Learning, vol.4, issue.5/6, pp.5-6304, 2012.
DOI : 10.1504/IJTEL.2012.051816

URL : http://oro.open.ac.uk/36374/1/IJTEL40501_Ferguson%20Jan%202013.pdf

. Gama, A survey on concept drift adaptation, ACM Computing Surveys, vol.46, issue.4, p.44, 2014.
DOI : 10.1109/TNNLS.2012.2236570

URL : http://eprints.bournemouth.ac.uk/22491/1/ACM%20computing%20surveys.pdf

. Garrido, On the use of case-based planning for e-learning personalization, Expert Systems with Applications, vol.60, pp.1-15, 2016.
DOI : 10.1016/j.eswa.2016.04.030

. Goyal, Discovering leaders from community actions, Proceeding of the 17th ACM conference on Information and knowledge mining, CIKM '08, pp.499-508, 2008.
DOI : 10.1145/1458082.1458149

URL : http://www-kdd.isti.cnr.it/~bonchi/fp0711-goyal.pdf

. Gras, Identification des utilisateurs atypiques dans les systèmes de recommandation sociale, EGC -Extraction et Gestion de Connaissances, 2015.

. Gras, Identifying Users with Atypical Preferences to Anticipate Inaccurate Recommendations, Proceedings of the 11th International Conference on Web Information Systems and Technologies, 2015.
DOI : 10.5220/0005412703810389

URL : https://hal.archives-ouvertes.fr/hal-01254172

. Gras, WEBIST (Revised Selected Papers), chapter When Users with Preferences Different from Others Get Inaccurate Recommendations, 2015.
DOI : 10.1007/978-3-319-30996-5_10

. Gras, Identifying Grey Sheep Users in Collaborative Filtering, Proceedings of the 2016 Conference on User Modeling Adaptation and Personalization, UMAP '16, 2016.
DOI : 10.1007/978-1-4899-3324-9

URL : https://hal.archives-ouvertes.fr/hal-01303284

. Gras, Can Matrix Factorization Improve the Accuracy of Recommendations Provided to Grey Sheep Users?, Proceedings of the 13th International Conference on Web Information Systems and Technologies, pp.88-96, 2017.
DOI : 10.5220/0006302700880096

URL : https://hal.archives-ouvertes.fr/hal-01569004

. Gröger, Prescriptive Analytics for Recommendation-Based Business Process Optimization, International Conference on Business Information Systems, 2014.
DOI : 10.1007/978-3-319-06695-0_3

. Guo, Merging trust in collaborative filtering to alleviate data sparsity and cold start. Knowledge-Based Systems, pp.57-68, 2014.
DOI : 10.1016/j.knosys.2013.12.007

K. Han, J. Han, and M. Kamber, Data Mining, 2006.
DOI : 10.1145/233269.233324

URL : https://hal.archives-ouvertes.fr/hal-01534761

. Han, , 2001.

. Prefixspan, Mining sequential patterns efficiently by prefix-projected pattern growth, proceedings of the 17th international conference on data engineering, pp.215-224

. Han, Mining frequent patterns without candidate generation, ACM SIGMOD Record, vol.29, issue.2, pp.1-12, 2000.
DOI : 10.1145/335191.335372

N. Henze and W. Nejdl, A logical characterization of adaptive educational hypermedia. Hypermedia -Special issue : Adaptive hypermedia in the age of the adaptive web, pp.77-113, 2004.

. Hu, Collaborative Filtering for Implicit Feedback Datasets, 2008 Eighth IEEE International Conference on Data Mining, pp.263-272, 2008.
DOI : 10.1109/ICDM.2008.22

. Huang, The SPHINX-II speech recognition system: an overview, Computer Speech & Language, vol.7, issue.2, pp.137-148, 1992.
DOI : 10.1006/csla.1993.1007

. Huptych, Measures for recommendations based on past students' activity, Proceedings of the Seventh International Learning Analytics & Knowledge Conference on, LAK '17, 2017.
DOI : 10.1016/j.eswa.2008.01.066

. Jannach, Recommender systems---, Communications of the ACM, vol.59, issue.11, pp.94-102, 2016.
DOI : 10.1145/223904.223931

. Jawaheer, Comparison of implicit and explicit feedback from an online music recommendation service, Proceedings of the 1st International Workshop on Information Heterogeneity and Fusion in Recommender Systems, HetRec '10, pp.47-51, 2010.
DOI : 10.1145/1869446.1869453

F. Jelinek, . J. Ibm-t, . Watson-research, and . Center, SELF-ORGANIZED LANGUAGE MODELING FOR SPEECH RECOGNITION, Continuous Speech Recognition Group, 1985.
DOI : 10.1016/B978-0-08-051584-7.50045-0

F. Jelinek, Statistical Methods for Speech Recognition, 1997.

. Johnson, , 2012.

. Jones, An Exploratory Work in Using Comparisons Instead of Ratings, Proc. of the 12th International Conference on Electronic Commerce and Web Technologies, pp.184-195, 2011.
DOI : 10.1016/S0001-6918(99)00050-5

. Jones, Comparisons Instead of Ratings: Towards More Stable Preferences, 2011 IEEE/WIC/ACM International Conferences on Web Intelligence and Intelligent Agent Technology, pp.451-456, 2011.
DOI : 10.1109/WI-IAT.2011.13

. Jones, Improving reliability of user preferences: Comparing instead of rating, 2011 Sixth International Conference on Digital Information Management, pp.316-321, 2011.
DOI : 10.1109/ICDIM.2011.6093367

. Jones, Initial Perspectives from Preferences Expressed through Comparisons, The 14th International Conference on Human-Computer Interaction -HCI International 2011, pp.33-37, 2011.
DOI : 10.1145/1839294.1839342

URL : https://hal.archives-ouvertes.fr/inria-00579606

. Jurafsky, . Martin, D. Jurafsky, and J. H. Martin, Speech and Language Processing, 2008.

S. Karampiperis, P. Karampiperis, and D. Sampson, Adaptive learning resources sequencing in educational hypermedia systems, Educational Technology and society, vol.8, issue.4, 2005.

. Katz, . Lazarsfeld, E. Katz, and P. Lazarsfeld, Personal influence : The part played by people in the flow of mass communications, 1955.

S. Katz, Estimation of probabilities from sparse data for the language model component of a speech recognizer, IEEE Transactions on Acoustics, Speech, and Signal Processing, vol.35, issue.3, 1987.
DOI : 10.1109/TASSP.1987.1165125

D. Kelly and J. Teevan, Implicit feedback for inferring user preference, ACM SIGIR Forum, vol.37, issue.2, pp.18-28, 2003.
DOI : 10.1145/959258.959260

. Konstan, J. A. Konstan, and J. Riedl, Recommender systems: from algorithms to user experience, User Modeling and User-Adapted Interaction, vol.21, issue.2, pp.101-123, 2012.
DOI : 10.1137/S0895479898344443

. Koren, Matrix Factorization Techniques for Recommender Systems, Computer, vol.42, issue.8, pp.4230-4267, 2009.
DOI : 10.1109/MC.2009.263

. Kuflik, Evaluating Rating Scales Personality, pp.310-315, 2012.
DOI : 10.1007/978-3-642-31454-4_27

D. Kuhn, R. Mori-]-kuhn, D. Mori, and R. , A cache-based natural language model for speech recognition, IEEE Transactions on Pattern Analysis and Machine Intelligence, vol.12, issue.6, pp.570-583, 1990.
DOI : 10.1109/34.56193

. Lafferty, Conditional random fields : Probabilistic models for segmenting and labeling sequence data, 18th International Conf on Machine Learning (ICML), pp.282-289, 2001.

. Langlois, Événements impossibles en modélisation stochastique du langage, Traitement Automatique des Langues, vol.44, issue.1, pp.33-61, 2003.

, Article dans revue scientifique avec comité de lecture

E. Laporte, Symbolic Natural Language Processing, Lothaire, editor, Applied Combinatorics on Words, pp.164-209, 2005.
URL : https://hal.archives-ouvertes.fr/hal-00145253

H. Lenhart, P. Lenhart, and D. Herzog, Combining content-based and collaborative filtering for personalized sports news recommendations, Proceedings of the 3rd Workshop on New Trends in Content-Based Recommender Systems co-located with ACM Conference on Recommender Systems, pp.3-10, 2016.

. Li, Recommendation Algorithm based on Link Prediction and Domain Knowledge in Retail Transactions, 2nd International Conference on Information Technology and Quantitative Management, pp.875-881, 2014.
DOI : 10.1016/j.procs.2014.05.339

. Li, Dynamic Adaptation Strategies for Long-Term and Short-Term User Profile to Personalize Search, pp.228-240, 2007.
DOI : 10.1007/978-3-540-72524-4_26

K. Li, Q. Li, and B. Kim, Clustering approach to hybrid recommendation, Proceedings of IEEE/WIC International Conference on Web Intelligence (WI'03)

D. Liben-nowell and J. Kleinberg, The link prediction problem for social networks, Proceedings of the Twelfth International Conference on Information and Knowledge Management, CIKM'03, pp.556-559, 2003.

. Lika, Facing the cold start problem in recommender systems, Expert Systems with Applications, vol.41, issue.4, pp.2065-2073, 2014.
DOI : 10.1016/j.eswa.2013.09.005

. Lin, Personalized news recommendation via implicit social experts, Information Sciences, vol.254, pp.1-18, 2014.
DOI : 10.1016/j.ins.2013.08.034

R. Lin, J. Lin, and D. Ryaboy, Scaling big data mining infrastructure, ACM SIGKDD Explorations Newsletter, vol.14, issue.2, pp.6-19, 2013.
DOI : 10.1145/2481244.2481247

. Liu, Wisdom of the better few, Proceedings of the fifth ACM conference on Recommender systems, RecSys '11, pp.37-44, 2011.
DOI : 10.1145/2043932.2043943

P. Long and G. Siemens, Penetrating the fog : analytics in learning and education, EDUCAUSE Review, 2011.

N. R. Mabroukeh and C. I. Ezeife, A taxonomy of sequential pattern mining algorithms, ACM Computing Surveys, vol.43, issue.1, pp.1-3, 2010.
DOI : 10.1145/1824795.1824798

A. Majumdar, https ://elearningindustry.com/creating-elearning-varying- learner-profiles-5-learners-know, retrieved on 29th, 2017.

. Maksai, Predicting Online Performance of News Recommender Systems Through Richer Evaluation Metrics, Proceedings of the 9th ACM Conference on Recommender Systems, RecSys '15, pp.179-186, 2015.
DOI : 10.1145/1060745.1060754

. Mannila, Discovery of frequent episodes in event sequences, Data Mining and Knowledge Discovery, vol.1, issue.3, pp.259-289, 1997.
DOI : 10.1023/A:1009748302351

. Mazumdar, An effective poi recommendation in various cold-start scenarios, The 22nd International Conference on Management of Data (COMAD), 2017.

S. Mcquiggan, J. Mcquiggan, and A. W. Sapp, Implement, Improve and Expand Your Statewide Longitudinal Data System : Creating a Culture of Data in Education, 2014.
DOI : 10.1002/9781118841563

. Middleton, Ontological user profiling in recommender systems, ACM Transactions on Information Systems, vol.22, issue.1, pp.54-88, 2004.
DOI : 10.1145/963770.963773

URL : https://eprints.soton.ac.uk/258926/1/tois2004.pdf

Z. Min, F. Min, and W. Zhu, Granular association rules for multi-valued data, 2013 26th IEEE Canadian Conference on Electrical and Computer Engineering (CCECE), pp.1-5, 2013.
DOI : 10.1109/CCECE.2013.6567838

B. Mobasher, Data Mining for Web Personalization, LNCS, vol.4321, pp.90-135, 2007.
DOI : 10.1007/978-3-540-72079-9_3

. Mobasher, sing sequential and non-sequential patterns in predictive web usage mining tasks, ICDM, pp.669-672, 2002.
DOI : 10.1109/icdm.2002.1184025

M. Nakagawa and B. Mobasher, Impact of Site Characteristics on Recommendation Models Based On Association Rules and Sequental Patterns, Intelligent Techniques for Web Personalization, 2003.

S. S. Banu, Predicting user's web navigation behavior using hybrid approach, International Conference on Advanced Computing Technologies and Applications (ICACTA), pp.3-12, 2015.

. Newell, The r??le of natural language processing in alternative and augmentative communication, Natural Language Engineering, vol.4, issue.1, pp.1-16, 1998.
DOI : 10.1017/S135132499800182X

M. , A new collaborative filtering approach for increasing the aggregate diversity of recommender systems, Proceedings of the 19th ACM SIGKDD international conference on Knowledge discovery and data mining, pp.955-963, 2013.

. Nowakowski, Technical and pedagogical feedback on the deployment of an ePortfolio. Models of the uses, analysis and perspectives, 10th ePorftolio and Identity conference -ePIC 2012, pp.177-185, 2012.
URL : https://hal.archives-ouvertes.fr/hal-00770013

. Nowakowski, P2CeL -Collaborative Knowledge Construction and eLearning : an Approach Based on Semantic Wikis, Online Educa -15th International Conference on Technology Supported Learning and Training, 2009.
URL : https://hal.archives-ouvertes.fr/inria-00436731

. Nowakowski, Towards Recommender Systems Based on Kalman Filters -A new Approach by State Space Modeling, 6th International Conference on Web Information Systems and Technologies -WEBIST 2010, pp.345-349, 2010.
URL : https://hal.archives-ouvertes.fr/inria-00548800

. Nowakowski, Production collaborative de connaissances et eLearning : une approche par wikis sociaux sémantiques, 7ème Colloque Technologies de l'Information et de la Communication pour l'Enseignement -TICE 2010, 2010.

. Palchenko, Using n-step matrix factorization for solving new user cold-start problem, 9th IEEE International Conference on Intelligent Data Acquisition and Advanced Computing Systems : Technology and Applications (IDAACS'17), 2017.

. Pan, Transfer learning in collaborative filtering for sparsity reduction, Association for the Advancement of Artificial Intelligence, 2010.

. Pei, Constraint-based sequential pattern mining: the pattern-growth methods, Journal of Intelligent Information Systems, vol.42, issue.1-2, pp.133-160, 2007.
DOI : 10.1007/s10844-006-0006-z

H. Pereira, A. L. Pereira, and E. R. Hruschka, Simultaneous co-clustering and learning to address the cold start problem in recommender systems, Knowledge-Based Systems, vol.82, pp.11-19, 2015.
DOI : 10.1016/j.knosys.2015.02.016

. Perrin, Utilisation d'invariants pour une médiation inter-domaines de modèles utilisateurs : ressources invariantes et invariants sémantiques, 12e Conférence Internationale Francophone sur l'Extraction et la Gestion de Connaissance, 2012.

. Pessiot, , 2006.

, Factorisation en matrices non-négatives pour le filtrage collaboratif, Proceedings of 3rd Conference en Recherche d'Information et Applications, pp.315-326

P. Pitkow, J. Pitkow, and P. Pirolli, Mining Longest Repeating Subsequences to Predict World Wide Web Surfing, USITS'99 : Proceedings of the 2nd conference on USENIX Symposium on Internet Technologies and Systems, pp.139-150, 1999.

C. Ponte, J. Ponte, and W. B. Croft, A language modeling approach to information retrieval, Proceedings of the ACM SIGIR'98, pp.275-281, 1998.

J. Potamianos, G. Potamianos, and F. Jelinek, A study of n-gram and decision tree letter language modeling methods, Speech Communication, vol.24, issue.3, pp.171-192, 1998.
DOI : 10.1016/S0167-6393(98)00018-1

R. Quillian, A notation for representing conceptual information : An application to semantics and mechanical english paraphrasing, System Development Corporation, p.1395, 1963.

L. Rabiner, A tutorial on hidden markov models and selected applications in speech recognition, pp.257-286, 1989.

. Rafferty, Faster Teaching via POMDP Planning, Cognitive Science, vol.24, issue.2, pp.1-43, 2015.
DOI : 10.1016/j.csl.2009.04.001

. Rajni, . Malaya, J. Rajni, and D. B. Malaya, Predictive analytics in a higher education context. IT Professional, pp.24-33, 2015.

. Ransbotham, Minding the analytics gap, 2015.

A. M. Rashid, Mining influence in recommender systems, 2007.

L. Razmerita and A. Brun, Assigning Students in Groups : Selfformed Groups versus Automatically-formed Groups, 7ème Colloque Technologies de l'Information et de la Communication pour l'Enseignement -TICE 2010, 2010.
URL : https://hal.archives-ouvertes.fr/inria-00597278

B. Razmerita, L. Razmerita, and A. Brun, Collaborative Learning in Heterogeneous Classes : Towards a Group Formation Methodology, International Conference on Computer Supported Education, pp.189-194, 2011.
URL : https://hal.archives-ouvertes.fr/inria-00580118

R. , S. Reilly, R. Sharkey, and N. , Connectionist approaches to natural language, The American Journal of Psychology, vol.107, issue.2, pp.291-299, 1992.

G. Reynolds, Information Technology for Managers. Cengage Learning, 2016.

R. Rosenfeld, Two decades of statistical language modeling: where do we go from here?, Proceedings of the IEEE, vol.88, issue.8, 2000.
DOI : 10.1109/5.880083

R. , Online planning algorithms for pomdps, Journal of Artificial Intelligence Research, vol.32, issue.2, pp.663-704, 2008.

. Sahebi, . Cohen, S. Sahebi, and W. W. Cohen, Community-based recommendations : a solution to the cold start problem, Workshop on recommender systems and the social web, p.60, 2011.

. Sarwar, Recommender systems for large-scale e-commerce : Scalable neighborhood formation using clustering, The 5th Int. Conf. on Computer and Information Technology, 2002.

. Saveski, . Mantrach, M. Saveski, and A. Mantrach, Item cold-start recommendations, Proceedings of the 8th ACM Conference on Recommender systems, RecSys '14, pp.89-96, 2014.
DOI : 10.1145/2645710.2645751

. Schein, Methods and metrics for cold-start recommendations, Proceedings of the 25th annual international ACM SIGIR conference on Research and development in information retrieval , SIGIR '02, pp.253-260, 2002.
DOI : 10.1145/564376.564421

. Shani, . Gunawardana, G. Shani, and A. Gunawardana, Evaluating recommendation systems. Recommender systems handbook, pp.257-297, 2011.

. Shani, An MDP-Based Recommender System, JMLR : The Journal of Machine Learning Research, pp.453-460, 2005.

C. Shannon, A mathematical theory of communication, Bell Sys. Tech. Journal, vol.27, pp.398-403, 1948.

. Smaïli, Automatic and Manual Clustering for Large Vocabulary Speech Recognition : A Comparative Study, European Conference on Speech Communication and Technology (EUROSPEECH'99), pp.1795-1798, 1999.

R. Soltanpoor and T. Sellis, Prescriptive Analytics for Big Data, Australasian Database Conference, 2016.
DOI : 10.1162/089976601750264965

L. H. Son, Dealing with the new user cold-start problem in recommender systems: A comparative review, Information Systems, vol.58, pp.87-104, 2016.
DOI : 10.1016/j.is.2014.10.001

G. Souza, Supply chain analytics, Business Horizons, vol.57, issue.5, pp.595-605, 2014.
DOI : 10.1016/j.bushor.2014.06.004

A. Srikant, R. Srikant, and R. Agrawal, Mining sequential patterns: Generalizations and performance improvements, EDBT, pp.3-16, 1996.
DOI : 10.1007/BFb0014140

. Takács, Investigation of various matrix factorization methods for large recommender systems, Proceedings of the 2Nd KDD Workshop on Large-Scale Recommender Systems and the Netflix Prize Competition, NETFLIX '08, pp.1-68, 2008.

L. Terveen and W. Hill, Beyond recommender systems : Helping people help each other. HCI in the New Millenium, pp.487-509, 2001.

M. Tintarev, N. Tintarev, and J. Masthoff, A Survey of Explanations in Recommender Systems, 2007 IEEE 23rd International Conference on Data Engineering Workshop, pp.801-810, 2007.
DOI : 10.1109/ICDEW.2007.4401070

. Toussaint, Hierarchical pomdp controller optimization by likelihood maximization, UAI, pp.562-570, 2008.

A. Tsymbal, The problem of concept drift : definitions and related work, 2004.

C. Ullrich and E. Melis, Pedagogically founded courseware generation based on HTN-planning, Expert Systems with Applications, vol.36, issue.5, 2009.
DOI : 10.1016/j.eswa.2008.12.043

T. Valente, Network models of the diffusion of innovations, Computational and Mathematical Organization Theory, vol.2, issue.2, 1995.
DOI : 10.1007/BF00240425

. Van-barneveld, Analytics in higher education : Establishing a common language, EDUCAUSE learning initiative, vol.1, issue.1, p.l?ll, 2012.

J. Vassileva and R. Deters, Dynamic Courseware Generation on the WWW, British Journal of Educational Technology, vol.29, issue.1, 1998.
DOI : 10.1111/1467-8535.00041

K. Margaritis, Collaborative filtering enhanced by demographic correlation, Proceedings of the International Conference on Intelligent Systems Design and Applications, 2004.

. Wang, Mining concept-drifting data streams using ensemble classifiers, Proceedings of the ninth ACM SIGKDD international conference on Knowledge discovery and data mining , KDD '03, pp.226-235, 2003.
DOI : 10.1145/956750.956778

. Wang, COBA: A Credible and Co-clustering Filterbot for Cold-Start Recommendations, pp.467-476, 2012.
DOI : 10.1007/978-3-642-25658-5_56

. Webb, Characterizing concept drift, Data Mining and Knowledge Discovery, vol.23, issue.1, pp.964-994, 2016.
DOI : 10.1145/1401890.1401987

Y. Wei, X. Wei, and J. Yan, Learner Profile Design for Personalized E-Learning Systems, 2009 International Conference on Computational Intelligence and Software Engineering, pp.1-4, 2009.
DOI : 10.1109/CISE.2009.5363560

E. Whittaker and P. Woodland, Comparison of language modelling techniques for russian and english, Proceedings of ICSLP'98, 1998.

A. T. Wibowo, Generating Pseudotransactions for Improving Sparse Matrix Factorization, Proceedings of the 10th ACM Conference on Recommender Systems, RecSys '16, pp.439-442, 2016.
DOI : 10.1145/2009916.2009961

. Wilson, Learning analytics: challenges and limitations, Teaching in Higher Education, pp.1-17, 2017.
DOI : 10.5210/fm.v22i4.6872

. Wright, The use of sequential pattern mining to predict next prescribed medications, Journal of Biomedical Informatics, vol.53, pp.73-80, 2015.
DOI : 10.1016/j.jbi.2014.09.003

. Wu, A Fuzzy Tree Matching-Based Personalized E-Learning Recommender System, IEEE Transactions on Fuzzy Systems, vol.23, issue.6, pp.2412-2426, 2015.
DOI : 10.1109/TFUZZ.2015.2426201

. Xie, A link prediction approach for item recommendation with complex number. Knowledge-Based Systems, pp.148-158, 2015.
DOI : 10.1109/wi-iat.2014.35

H. Yang and S. Fong, Countering the concept-drift problems in big data by an incrementally optimized stream mining model, Journal of Systems and Software, vol.102, pp.158-166, 2015.
DOI : 10.1016/j.jss.2014.07.010

. Yoo, Persuasive Recommender Systems, 2012.
DOI : 10.1007/978-1-4614-4702-3

M. J. Zaki, Efficient enumeration of frequent sequences, Proceedings of the seventh international conference on Information and knowledge management , CIKM '98, pp.68-75, 1998.
DOI : 10.1145/288627.288643

M. J. Zaki, Sequence mining in categorical domains, Proceedings of the ninth international conference on Information and knowledge management , CIKM '00, pp.422-429, 2000.
DOI : 10.1145/354756.354849

. Zhang, Learning from Incomplete Ratings Using Non-negative Matrix Factorization, Proceedings of the 6th SIAM Conference on Data Mining, pp.548-552, 2006.
DOI : 10.1137/1.9781611972764.58

URL : http://www.siam.org/meetings/sdm06/proceedings/059zhangs2.pdf

. Zhang, Multi-domain collaborative filtering, Proceedings of the 26th Conference on Uncertainty in Artificial Intelligence (UAI), pp.725-732, 2010.

. Zimdars, Using Temporal Data for Making Recommendations, UAI, pp.580-588, 2001.