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\n\n \n \n \n \n \n \n Vers une approche Visual Analytics pour explorer les variantes de sujets d'un corpus.\n \n \n \n \n\n\n \n Médoc, N.; Ghoniem, M.; and Nadif, M.\n\n\n \n\n\n\n In
16ème Journées Francophones Extraction et Gestion des Connaissances, EGC 2016, 18-22 Janvier 2016, Reims, France, pages 539–540, 2016. \n
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@INPROCEEDINGS{DBLP:conf/f-egc/MedocGN16,\r\n author = {Nicolas M{\\'{e}}doc and Mohammad Ghoniem and Mohamed Nadif},\r\n title = {Vers une approche Visual Analytics pour explorer les variantes de\r\n\tsujets d'un corpus},\r\n booktitle = {16{\\`{e}}me Journ{\\'{e}}es Francophones Extraction et Gestion des\r\n\tConnaissances, {EGC} 2016, 18-22 Janvier 2016, Reims, France},\r\n year = {2016},\r\n pages = {539--540},\r\n bibsource = {dblp computer science bibliography, http://dblp.org},\r\n biburl = {http://dblp.uni-trier.de/rec/bib/conf/f-egc/MedocGN16},\r\n crossref = {DBLP:conf/f-egc/2016},\r\n timestamp = {Fri, 22 Jan 2016 10:19:37 +0100},\r\n url = {http://editions-rnti.fr/?inprocid=1002220}\r\n}\r\n\r\n
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\n\n \n \n \n \n \n Graph modularity maximization as an effective method for co-clustering text data.\n \n \n \n\n\n \n Ailem, M.; Role, F.; and Nadif, M.\n\n\n \n\n\n\n
Knowledge-Based Systems, 109: 160–173. 2016.\n
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@ARTICLE{ailem2016graph,\r\n author = {Ailem, Melissa and Role, Fran{\\c{c}}ois and Nadif, Mohamed},\r\n title = {Graph modularity maximization as an effective method for co-clustering\r\n\ttext data},\r\n journal = {Knowledge-Based Systems},\r\n year = {2016},\r\n volume = {109},\r\n pages = {160--173},\r\n publisher = {Elsevier}\r\n}\r\n\r\n
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\n\n \n \n \n \n \n Unsupervised Text Mining for Assessing and Augmenting GWAS Results.\n \n \n \n\n\n \n Ailem, M.; Role, F.; Nadif, M.; and Demenais, F.\n\n\n \n\n\n\n
Journal of Biomedical Informatics, 60: 252-259. 2016.\n
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@ARTICLE{ailem_jbi_2016,\r\n author = {Ailem, Melissa and Role, Fran{\\c{c}}ois and Nadif, Mohamed and Demenais,\r\n\tFlorence},\r\n title = {Unsupervised Text Mining for Assessing and Augmenting GWAS Results},\r\n journal = {Journal of Biomedical Informatics},\r\n year = {2016},\r\n volume = {60},\r\n pages = {252-259},\r\n publisher = {Elsevier}\r\n}\r\n\r\n
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\n\n \n \n \n \n \n Power Simultaneous Spectral Data Embedding and Clustering.\n \n \n \n\n\n \n Allab, K.; Labiod, L.; and Nadif, M.\n\n\n \n\n\n\n In
SIAM International Conference on Data Mining (SDM'16), pages 270-278, Miami, FL, United States, 2016. \n
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@INPROCEEDINGS{Allab_16a,\r\n author = {Allab, Kais and Labiod, Lazhar and Nadif, Mohamed},\r\n title = {Power Simultaneous Spectral Data Embedding and Clustering},\r\n booktitle = {SIAM International Conference on Data Mining (SDM'16)},\r\n year = {2016},\r\n pages = {270-278},\r\n address = {Miami, FL, United States}\r\n}\r\n\r\n
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\n\n \n \n \n \n \n SemiNMF-PCA framework for Sparse Data Co-clustering.\n \n \n \n\n\n \n Allab, K.; Labiod, L.; and Nadif, M.\n\n\n \n\n\n\n In
ACM International Conference on Information and Knowledge Management (CIKM'16), pages 347-356, Indianapolis-IN-United States, 2016. \n
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@INPROCEEDINGS{Allab_16b,\r\n author = {Allab, Kais and Labiod, Lazhar and Nadif, Mohamed},\r\n title = {SemiNMF-PCA framework for Sparse Data Co-clustering},\r\n booktitle = {ACM International Conference on Information and Knowledge Management\r\n\t(CIKM'16)},\r\n year = {2016},\r\n pages = {347-356},\r\n address = {Indianapolis-IN-United States}\r\n}\r\n\r\n
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\n\n \n \n \n \n \n Bi-stochastic Matrix Approximation Framework for Data Co-clustering.\n \n \n \n\n\n \n Labiod, L.; and Nadif, M.\n\n\n \n\n\n\n In
Advances in Intelligent Data Analysis (IDA'16), volume 9897, of
Lecture Notes in Computer Science, pages 273-283, 2016. Springer\n
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@INPROCEEDINGS{Labiod_IDA16,\r\n author = {Lazhar Labiod and Mohamed Nadif},\r\n title = {Bi-stochastic Matrix Approximation Framework for Data Co-clustering},\r\n booktitle = {Advances in Intelligent Data Analysis (IDA'16)},\r\n year = {2016},\r\n volume = {9897},\r\n series = {Lecture Notes in Computer Science},\r\n pages = {273-283},\r\n publisher = {Springer}\r\n}\r\n\r\n
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\n\n \n \n \n \n \n \n Diagonal latent block model for binary data.\n \n \n \n \n\n\n \n Laclau, C.; and Nadif, M.\n\n\n \n\n\n\n
Statistics and Computing,1–19. 2016.\n
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@ARTICLE{Laclau2016,\r\n author = {Laclau, Charlotte and Nadif, Mohamed},\r\n title = {Diagonal latent block model for binary data},\r\n journal = {Statistics and Computing},\r\n year = {2016},\r\n pages = {1--19},\r\n doi = {10.1007/s11222-016-9677-7},\r\n issn = {1573-1375},\r\n url = {http://dx.doi.org/10.1007/s11222-016-9677-7}\r\n}\r\n\r\n
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\n\n \n \n \n \n \n \n Hard and fuzzy diagonal co-clustering for document-term partitioning .\n \n \n \n \n\n\n \n Laclau, C.; and Nadif, M.\n\n\n \n\n\n\n
Neurocomputing , 193: 133 - 147. 2016.\n
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@ARTICLE{Laclau2016133,\r\n author = {Charlotte Laclau and Mohamed Nadif},\r\n title = {Hard and fuzzy diagonal co-clustering for document-term partitioning\r\n\t},\r\n journal = {Neurocomputing },\r\n year = {2016},\r\n volume = {193},\r\n pages = {133 - 147},\r\n doi = {http://dx.doi.org/10.1016/j.neucom.2016.02.003},\r\n issn = {0925-2312},\r\n keywords = {Co-clustering},\r\n url = {http://www.sciencedirect.com/science/article/pii/S0925231216001818}\r\n}\r\n\r\n
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\n\n \n \n \n \n \n Generalized topographic block model .\n \n \n \n\n\n \n Priam, R.; Nadif, M.; and Govaert, G.\n\n\n \n\n\n\n
Neurocomputing , 173, Part 2: 442 - 449. 2016.\n
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@ARTICLE{Priam_16a,\r\n author = {Rodolphe Priam and Mohamed Nadif and Gérard Govaert},\r\n title = {Generalized topographic block model },\r\n journal = {Neurocomputing },\r\n year = {2016},\r\n volume = {173, Part 2},\r\n pages = {442 - 449}\r\n}\r\n\r\n
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\n\n \n \n \n \n \n A dynamic collaborative filtering system via a weighted clustering approach .\n \n \n \n\n\n \n Salah, A.; Rogovschi, N.; and Nadif, M.\n\n\n \n\n\n\n
Neurocomputing , 175, Part A: 206 - 215. 2016.\n
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@ARTICLE{Salah16a,\r\n author = {Aghiles Salah and Nicoleta Rogovschi and Mohamed Nadif},\r\n title = {A dynamic collaborative filtering system via a weighted clustering\r\n\tapproach },\r\n journal = {Neurocomputing },\r\n year = {2016},\r\n volume = {175, Part A},\r\n pages = {206 - 215}\r\n}\r\n\r\n
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\n\n \n \n \n \n \n \n Model-based Co-clustering for High Dimensional Sparse Data.\n \n \n \n \n\n\n \n Salah, A.; Rogovschi, N.; and Nadif, M.\n\n\n \n\n\n\n In
Proceedings of the 19th International Conference on Artificial Intelligence and Statistics (AISTAT'16), pages 866–874, Cadiz, Spain, 2016. \n
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@INPROCEEDINGS{salah16b,\r\n author = {Salah, Aghiles and Rogovschi, Nicoleta and Nadif, Mohamed},\r\n title = {Model-based Co-clustering for High Dimensional Sparse Data},\r\n booktitle = {Proceedings of the 19th International Conference on Artificial Intelligence\r\n\tand Statistics (AISTAT'16)},\r\n year = {2016},\r\n pages = {866--874},\r\n address = {Cadiz, Spain},\r\n url_link = {http://www.jmlr.org/proceedings/papers/v51/salah16.html},\r\n url_paper = {http://www.jmlr.org/proceedings/papers/v51/salah16.pdf}\r\n}\r\n\r\n
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\n\n \n \n \n \n \n \n Stochastic Co-clustering for Document-Term Data.\n \n \n \n \n\n\n \n Salah, A.; Rogovschi, N.; and Nadif, M.\n\n\n \n\n\n\n In
Proceedings of the 2016 SIAM International Conference on Data Mining (SDM'16), pages 306–314, Miami, FL, United States, 2016. SIAM\n
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@inproceedings{salah16c,\r\n title={Stochastic Co-clustering for Document-Term Data},\r\n author={Salah, Aghiles and Rogovschi, Nicoleta and Nadif, Mohamed},\r\n booktitle={Proceedings of the 2016 SIAM International Conference on Data Mining (SDM'16)},\r\n pages={306--314},\r\n year={2016},\r\n address = {Miami, FL, United States},\r\n url_Paper = {http://epubs.siam.org/doi/pdf/10.1137/1.9781611974348.35},\r\n url_Link = {http://epubs.siam.org/doi/abs/10.1137/1.9781611974348.35},\r\n organization={SIAM}\r\n}\r\n\r\n
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