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251 results on '"Ben Yahia S"'

5. Ocular manifestations associated with murine typhus

Author

Khairallah, M., Ben Yahia, S., Toumi, A., Jelliti, B., Loussaief, C., Romdhane, F.B., Messaoud, R., and Chakroun, M.

Subjects
Ocular manifestations of general diseases -- Research, Health
Published
2009

13. RakSOR: Ranking of Ontology Reasoners Based on Predicted Performances

Author

Alaya, Nourhène, Ben Yahia, S., Lamolle, Myriam, Laboratoire d'Informatique Avancée de Saint-Denis (LIASD), and Université Paris 8 Vincennes-Saint-Denis (UP8)

Subjects
[INFO]Computer Science [cs], ComputingMilieux_MISCELLANEOUS
Abstract

International audience

Published
2016

14. Strategy for the management of uncomplicated retinal detachments: the European vitreo-retinal society retinal detachment study report 1

Author

BENMERZOUGA N, METTI F, RAZZARI A, MIESBAUER P, SCHÖNHERR U, ZEYNALOVA Z, BASHIR SJ, JACOB J, KOCH P, LADHA R, SMETS E, STALMANS P, DARE A, DEVENYI R, LAM WC, SHAHEEDA M, POTAMITIS T, CHRISTENSEN SR, RAYES E, MORTADA H, SHOUMAN A, HOLM M, ALBINET P, AMAR JP, BECQUET F, BERROD JP, BOULZE M, BOSCHER C, COURJARET JC, DENION E, FOURMAUX, E, GUIGOU S, HAMON F, LAFONTAINE PO, LE ROUIC JF, LEYNAUD JL, NOCHEZ Y, PERONE JM, RYSANEK B, SOYEUR R, BOPP S, BRIX A, HÖHN F, KUSSEROW C, LUCKE K, MOHR A, SCHÜLER A, WEINBERGER A, GOTZARIDIS S, KARATZENIS D, STEFANIOTOU M, K. TSILIMBARIS MK, TSOURIS D, TSANG CW, GABOR R, SZIJARTO Z, BABU N, BANKER AS, BAPAYE M, KELKAR A, ENTEZARI, M, FATEH MOGHADAM HF, RAMEZANI A, SAFARPOUR LIMA B, OMER K, BOSCIA F, CHIARA FRENO M, CIAN R, DONVITO G, FACINO M, LESNONI G, LIUZZI, F, METE M, MININNI F, MOCHI B, PRIMAVERA V, PERTILE G, TURCO I, VASTARELLA P, FONG K, LEE M, VP LOO A, ARAGON HARRISON O, FLORES AGUILAR M, LOPEZ MONTERO LM, LOPEZCARASA HERNANDEZ G, VELASCO I, BOEYDEN V, BOSSCHA M, DE VRIES KNOPPERT W, LINDSTEDT, E. RENARDEL DE LAVALETTE VW, VAN DEN BIESEN PR, ALHASSAN M, BAERLAND TP, BOBER AM, FORSAA V, FOSSEN K, VARHAUG P, ATIENZA J.r. NF, CISIECKI S, FRYCZKOWSKI P, KOWAL LANGE A, MICHALEWSKA Z, MICHALEWSKI J, NAWROCKI J, NOWOSIELSKA A, ODROBINA D, PIETRAS TRZPIEL M, ZAKRZEWSKA A, MEIRELES A, TEIXEIRA S, ELSHAFEI M, DANIELESCU C, TALU S, ALTYNBAEV U, GORIN A, SEREJINE I, EL DEEB M, DAVIDOVIC S, IGNJATOVIC Z, STEFANICKOVA J, VENTER L, CHANG W, JO YL, KIM JY, LEE J, LIM ST, SAGONG M, ASCASO FJ, CASTRO J, CORDOVES L. DESCO ESTEBAN C, MORENO MANRESA J, VILAPLANA D, JANIEC S, TOMIC Z, BEN YAHIA S, ACAR N, GÜNGEL H, KAPRAN Z, OSMANBASOGLU O, OZDEK S, TOPBAS S, TOTAN Y, ÜNVER YB, CHICHUR D, DOBROVOLSKEY O, KOZLOVSKA I, LYTVYNCHUK L, PHYLYPCHUK O, POSTOLOVSKA A, SERGIIENKO A, SHEVCHYK V, WINDER S, CULOTTA J, KIM S, KING J, KURUP SK, LIN SJ, PACURARIU R, ROTH D, SINCLAIR S, WEBER P, DOAN H, TUNG T., ROMANO, MARIO, Benmerzouga, N, Metti, F, Razzari, A, Miesbauer, P, Schönherr, U, Zeynalova, Z, Bashir, Sj, Jacob, J, Koch, P, Ladha, R, Smets, E, Stalmans, P, Dare, A, Devenyi, R, Lam, Wc, Shaheeda, M, Potamitis, T, Christensen, Sr, Rayes, E, Mortada, H, Shouman, A, Holm, M, Albinet, P, Amar, Jp, Becquet, F, Berrod, Jp, Boulze, M, Boscher, C, Courjaret, Jc, Denion, E, Fourmaux, E, Guigou, S, Hamon, F, Lafontaine, Po, LE ROUIC, Jf, Leynaud, Jl, Nochez, Y, Perone, Jm, Rysanek, B, Soyeur, R, Bopp, S, Brix, A, Höhn, F, Kusserow, C, Lucke, K, Mohr, A, Schüler, A, Weinberger, A, Gotzaridis, S, Karatzenis, D, Stefaniotou, M, K., TSILIMBARIS MK, Tsouris, D, Tsang, Cw, Gabor, R, Szijarto, Z, Babu, N, Banker, A, Bapaye, M, Kelkar, A, Entezari, M, FATEH MOGHADAM, Hf, Ramezani, A, SAFARPOUR LIMA, B, Omer, K, Boscia, F, CHIARA FRENO, M, Cian, R, Donvito, G, Facino, M, Lesnoni, G, Liuzzi, F, Mete, M, Mininni, F, Mochi, B, Primavera, V, Romano, Mario, Pertile, G, Turco, I, Vastarella, P, Fong, K, Lee, M, VP LOO, A, ARAGON HARRISON, O, FLORES AGUILAR, M, LOPEZ MONTERO, Lm, LOPEZCARASA HERNANDEZ, G, Velasco, I, Boeyden, V, Bosscha, M, DE VRIES KNOPPERT, W, Lindstedt, E., RENARDEL DE LAVALETTE VW, VAN DEN BIESEN, Pr, Alhassan, M, Baerland, Tp, Bober, Am, Forsaa, V, Fossen, K, Varhaug, P, ATIENZA J. r., Nf, Cisiecki, S, Fryczkowski, P, KOWAL LANGE, A, Michalewska, Z, Michalewski, J, Nawrocki, J, Nowosielska, A, Odrobina, D, PIETRAS TRZPIEL, M, Zakrzewska, A, Meireles, A, Teixeira, S, Elshafei, M, Danielescu, C, Talu, S, Altynbaev, U, Gorin, A, Serejine, I, EL DEEB, M, Davidovic, S, Ignjatovic, Z, Stefanickova, J, Venter, L, Chang, W, Jo, Yl, Kim, Jy, Lee, J, Lim, St, Sagong, M, Ascaso, Fj, Castro, J, CORDOVES L., DESCO ESTEBAN C, MORENO MANRESA, J, Vilaplana, D, Janiec, S, Tomic, Z, BEN YAHIA, S, Acar, N, Güngel, H, Kapran, Z, Osmanbasoglu, O, Ozdek, S, Topbas, S, Totan, Y, Ünver, Yb, Chichur, D, Dobrovolskey, O, Kozlovska, I, Lytvynchuk, L, Phylypchuk, O, Postolovska, A, Sergiienko, A, Shevchyk, V, Winder, S, Culotta, J, Kim, S, King, J, Kurup, Sk, Lin, Sj, Pacurariu, R, Roth, D, Sinclair, S, Weber, P, Doan, H, and Tung, T.

Abstract

OBJECTIVE: To study success and failure in the treatment of uncomplicated rhegmatogenous retinal detachments (RRDs). DESIGN: Nonrandomized, multicenter retrospective study. PARTICIPANTS: One hundred seventy-six surgeons from 48 countries spanning 5 continents provided information on the primary procedures for 7678 cases of RRDs including 4179 patients with uncomplicated RRDs. METHODS: Reported data included specific clinical findings, the method of repair, and the outcome after intervention. MAIN OUTCOME MEASURES: Final failure of retinal detachment repair (level 1 failure rate), remaining silicone oil at the study's conclusion (level 2 failure rate), and need for additional procedures to repair the detachment (level 3 failure rate). RESULTS: Four thousand one hundred seventy-nine uncomplicated cases of RRD were included. Combining phakic, pseudophakic, and aphakic groups, those treated with scleral buckle alone (n = 1341) had a significantly lower final failure rate than those treated with vitrectomy, with or without a supplemental buckle (n = 2723; P = 0.04). In phakic patients, final failure rate was lower in the scleral buckle group compared with those who had vitrectomy, with or without a supplemental buckle (P = 0.028). In pseudophakic patients, the failure rate of the initial procedure was lower in the vitrectomy group compared with the scleral buckle group (P = 3×10(-8)). There was no statistically significant difference in failure rate between segmental (n = 721) and encircling (n = 351) buckles (P = 0.5). Those who underwent vitrectomy with a supplemental scleral buckle (n = 488) had an increased failure rate compared with those who underwent vitrectomy alone (n = 2235; P = 0.048). Pneumatic retinopexy was found to be comparable with scleral buckle when a retinal hole was present (P = 0.65), but not in cases with a flap tear (P = 0.034). CONCLUSIONS: In the treatment of uncomplicated phakic retinal detachments, repair using scleral buckle may be a good option. There was no significant difference between segmental versus 360-degree buckle. For pseudophakic uncomplicated retinal detachments, the surgeon should balance the risks and benefits of vitrectomy versus scleral buckle and keep in mind that the single-surgery reattachment rate may be higher with vitrectomy. However, if a vitrectomy is to be performed, these data suggest that a supplemental buckle is not helpful.

Published
2013

15. Strategy for the management of complex retinal detachments: the European vitreo-retinal society retinal detachment study report 2

Author

BENMERZOUGA N, METTI F, RAZZARI A, MIESBAUER P, SCHÖNHERR U, ZEYNALOVA Z, BASHIR SJ, JACOB J, KOCH P, LADHA R, SMETS E, STALMANS P, DARE A, DEVENYI R, LAM WC, SHAHEEDA M, POTAMITIS T, CHRISTENSEN SR, RAYES E, MORTADA H, SHOUMAN A, HOLM M, ALBINET P, AMAR JP, BECQUET F, BERROD JP, BOULZE M, BOSCHER C, COURJARET JC, DENION E, FOURMAUX, E, GUIGOU S, HAMON F, LAFONTAINE PO, LE ROUIC JF, LEYNAUD JL, NOCHEZ Y, PERONE JM, RYSANEK B, SOYEUR R, BOPP S, BRIX A, HÖHN F, KUSSEROW C, LUCKE K, MOHR A, SCHÜLER A, WEINBERGER A, GOTZARIDIS S, KARATZENIS D, STEFANIOTOU M, K. TSILIMBARIS MK, TSOURIS D, TSANG CW, GABOR R, SZIJARTO Z, BABU N, BANKER AS, BAPAYE M, KELKAR A, ENTEZARI, M, FATEH MOGHADAM HF, RAMEZANI A, SAFARPOUR LIMA B, OMER K, BOSCIA F, CHIARA FRENO M, CIAN R, DONVITO G, FACINO M, LESNONI G, LIUZZI, F, METE M, MININNI F, MOCHI B, PRIMAVERA V, PERTILE G, TURCO I, VASTARELLA P, FONG K, LEE M, VP LOO A, ARAGON HARRISON O, FLORES AGUILAR M, LOPEZ MONTERO LM, LOPEZCARASA HERNANDEZ G, VELASCO I, BOEYDEN V, BOSSCHA M, DE VRIES KNOPPERT W, LINDSTEDT, E. RENARDEL DE LAVALETTE VW, VAN DEN BIESEN PR, ALHASSAN M, BAERLAND TP, BOBER AM, FORSAA V, FOSSEN K, VARHAUG P, ATIENZA J.r. NF, CISIECKI S, FRYCZKOWSKI P, KOWAL LANGE A, MICHALEWSKA Z, MICHALEWSKI J, NAWROCKI J, NOWOSIELSKA A, ODROBINA D, PIETRAS TRZPIEL M, ZAKRZEWSKA A, MEIRELES A, TEIXEIRA S, ELSHAFEI M, DANIELESCU C, TALU S, ALTYNBAEV U, GORIN A, SEREJINE I, EL DEEB M, DAVIDOVIC S, IGNJATOVIC Z, STEFANICKOVA J, VENTER L, CHANG W, JO YL, KIM JY, LEE J, LIM ST, SAGONG M, ASCASO FJ, CASTRO J, CORDOVES L. DESCO ESTEBAN C, MORENO MANRESA J, VILAPLANA D, JANIEC S, TOMIC Z, BEN YAHIA S, ACAR N, GÜNGEL H, KAPRAN Z, OSMANBASOGLU O, OZDEK S, TOPBAS S, TOTAN Y, ÜNVER YB, CHICHUR D, DOBROVOLSKEY O, KOZLOVSKA I, LYTVYNCHUK L, PHYLYPCHUK O, POSTOLOVSKA A, SERGIIENKO A, SHEVCHYK V, WINDER S, CULOTTA J, KIM S, KING J, KURUP SK, LIN SJ, PACURARIU R, ROTH D, SINCLAIR S, WEBER P, DOAN H, TUNG T., ROMANO, MARIO, Benmerzouga, N, Metti, F, Razzari, A, Miesbauer, P, Schönherr, U, Zeynalova, Z, Bashir, Sj, Jacob, J, Koch, P, Ladha, R, Smets, E, Stalmans, P, Dare, A, Devenyi, R, Lam, Wc, Shaheeda, M, Potamitis, T, Christensen, Sr, Rayes, E, Mortada, H, Shouman, A, Holm, M, Albinet, P, Amar, Jp, Becquet, F, Berrod, Jp, Boulze, M, Boscher, C, Courjaret, Jc, Denion, E, Fourmaux, E, Guigou, S, Hamon, F, Lafontaine, Po, LE ROUIC, Jf, Leynaud, Jl, Nochez, Y, Perone, Jm, Rysanek, B, Soyeur, R, Bopp, S, Brix, A, Höhn, F, Kusserow, C, Lucke, K, Mohr, A, Schüler, A, Weinberger, A, Gotzaridis, S, Karatzenis, D, Stefaniotou, M, K., TSILIMBARIS MK, Tsouris, D, Tsang, Cw, Gabor, R, Szijarto, Z, Babu, N, Banker, A, Bapaye, M, Kelkar, A, Entezari, M, FATEH MOGHADAM, Hf, Ramezani, A, SAFARPOUR LIMA, B, Omer, K, Boscia, F, CHIARA FRENO, M, Cian, R, Donvito, G, Facino, M, Lesnoni, G, Liuzzi, F, Mete, M, Mininni, F, Mochi, B, Primavera, V, Romano, Mario, Pertile, G, Turco, I, Vastarella, P, Fong, K, Lee, M, VP LOO, A, ARAGON HARRISON, O, FLORES AGUILAR, M, LOPEZ MONTERO, Lm, LOPEZCARASA HERNANDEZ, G, Velasco, I, Boeyden, V, Bosscha, M, DE VRIES KNOPPERT, W, Lindstedt, E., RENARDEL DE LAVALETTE VW, VAN DEN BIESEN, Pr, Alhassan, M, Baerland, Tp, Bober, Am, Forsaa, V, Fossen, K, Varhaug, P, ATIENZA J. r., Nf, Cisiecki, S, Fryczkowski, P, KOWAL LANGE, A, Michalewska, Z, Michalewski, J, Nawrocki, J, Nowosielska, A, Odrobina, D, PIETRAS TRZPIEL, M, Zakrzewska, A, Meireles, A, Teixeira, S, Elshafei, M, Danielescu, C, Talu, S, Altynbaev, U, Gorin, A, Serejine, I, EL DEEB, M, Davidovic, S, Ignjatovic, Z, Stefanickova, J, Venter, L, Chang, W, Jo, Yl, Kim, Jy, Lee, J, Lim, St, Sagong, M, Ascaso, Fj, Castro, J, CORDOVES L., DESCO ESTEBAN C, MORENO MANRESA, J, Vilaplana, D, Janiec, S, Tomic, Z, BEN YAHIA, S, Acar, N, Güngel, H, Kapran, Z, Osmanbasoglu, O, Ozdek, S, Topbas, S, Totan, Y, Ünver, Yb, Chichur, D, Dobrovolskey, O, Kozlovska, I, Lytvynchuk, L, Phylypchuk, O, Postolovska, A, Sergiienko, A, Shevchyk, V, Winder, S, Culotta, J, Kim, S, King, J, Kurup, Sk, Lin, Sj, Pacurariu, R, Roth, D, Sinclair, S, Weber, P, Doan, H, and Tung, T.

Abstract

OBJECTIVE: To study the outcome of the treatment of complex rhegmatogenous retinal detachments (RRDs). DESIGN: Nonrandomized, multicenter, retrospective study. PARTICIPANTS: One hundred seventy-six surgeons from 48 countries spanning 5 continents reported primary procedures for 7678 RRDs. METHODS: Reported data included clinical manifestations, the method of repair, and the outcome. MAIN OUTCOME MEASURES: Failure of retinal detachment repair (level 1 failure rate), remaining silicone oil at the study's conclusion (level 2 failure rate), and need for additional procedures to repair the detachments (level 3 failure rate). RESULTS: The main categories of complex retinal detachments evaluated in this investigation were: (1) grade B proliferative vitreoretinopathy (PVR; n = 917), (2) grade C-1 PVR (n = 637), (3) choroidal detachment or significant hypotony (n = 578), (4) large or giant retinal tears (n = 1167), and (5) macular holes (n = 153). In grade B PVR, the level 1 failure rate was higher when treated with a scleral buckle alone versus vitrectomy (P = 0.0017). In grade C-1 PVR, there was no statistically significant difference in the level 1 failure rate between those treated with vitrectomy, with or without scleral buckle, and those treated with scleral buckle alone (P = 0.7). Vitrectomy with a supplemental buckle had an increased failure rate compared with those who did not receive a buckle (P = 0.007). There was no statistically significant difference in level 1 failure rate between tamponade with gas versus silicone oil in patients with grade B or C-1 PVR. Cases with choroidal detachment or hypotony treated with vitrectomy had a significantly lower failure rate versus treatment with scleral buckle alone (P = 0.0015). Large or giant retinal tears treated with vitrectomy also had a significantly lower failure rate versus treatment with scleral buckle (P = 7×10(-8)). CONCLUSIONS: In patients with retinal detachment, when choroidal detachment, hypotony, a large tear, or a giant tear is present, vitrectomy is the procedure of choice. In retinal detachments with PVR, tamponade with either gas or silicone oil can be considered. If a vitrectomy is to be performed, these data suggest that a supplemental buckle may not be helpful. FINANCIAL DISCLOSURE(S): The author(s) have no proprietary or commercial interest in any materials discussed in this article.

Published
2013

16. Hypergraph fuzzy minimals transversals mining: A new approach for social media recommendation

Author

Souid, H, Trabelsi, C, Pasi, G, Ben Yahia, S, Souid, H, Trabelsi, C, Pasi, G, and Ben Yahia, S

Abstract

User preference discovery aims to detect the patterns of user preferences for various topics of interest or items such as movie genre or category. Preferences discovery is a crucial stage in the development of intelligent personalization systems. Although a variety of studies have been proposed in the literature addressing a wide range of applications such as recommender systems or personalized search, only a few of them have considered the management of imprecision in the representation of user and item features. This paper aims to address the above issue by using fuzzy sets. The paper proposes a general framework for preferences discovery through fuzzy sets and fuzzy models and it introduces a new algorithm for representing and discovering fuzzy user interest profile. Based on the results of the empirical evaluation, the proposed approach outperforms two well-known recommendation approaches in terms of well-known quality assessment metrics, namely: discounted cumulative gain, precision, recall, as well as F1-measure.

Published
2017

18. An Aho-Corasick based assessment of algorithms generating failure deterministic finite automata

Author

Nxumalo, Madoda, Kourie, Derrick G., Cleophas, Loek, Watson, Bruce W., Ben Yahia, S., and Konecny, J.

Subjects
TheoryofComputation_COMPUTATIONBYABSTRACTDEVICES, TheoryofComputation_MATHEMATICALLOGICANDFORMALLANGUAGES, Aho-Corasick algorithm, Failure deterministic finite automaton
Abstract

The Aho-Corasick algorithm derives a failure deterministic finite automaton for finding matches of a finite set of keywords in a text. It has the minimum number of transitions needed for this task. The DFA-Homomorphic Algorithm (DHA) algorithm is more general, deriving from an arbitrary complete deterministic finite automaton a language-equivalent failure deterministic finite automaton. DHA takes formal concepts of a lattice as input. This lattice is built from a state/outtransition formal context that is derived from the complete deterministic finite automaton. In this paper, three general variants of the abstract DHA are benchmarked against the specialised Aho-Corasick algorithm. It is shown that when heuristics for these variants are suitably chosen, the minimality attained by the Aho-Corasick algorithm can be closely approximated. A published non-lattice-based algorithm is also shown to perform well in experiments.

Published
2015

22. SODA : Une approche structurelle pour l'alignement d'ontologies OWL-DL

Author

Zghal, Sami, Ben Yahia, S., Mephu Nguifo, Engelbert, Slimani, Y., Centre de Recherche en Informatique de Lens (CRIL), Université d'Artois (UA)-Centre National de la Recherche Scientifique (CNRS), Gargouri Faïez, Benslimane Djamel et Bourque Pierre, and Chevallier, Francois

Subjects
[INFO.INFO-AI] Computer Science [cs]/Artificial Intelligence [cs.AI], ComputingMilieux_MISCELLANEOUS, [INFO.INFO-AI]Computer Science [cs]/Artificial Intelligence [cs.AI]
Abstract

National audience

Published
2007

23. Les itemsets essentiels fermés: une nouvelle représentation concise

Author

Hamrouni, T., Denden, I., Ben Yahia, S., Mephu Nguifo, Engelbert, Slimani, Y., Centre de Recherche en Informatique de Lens (CRIL), Université d'Artois (UA)-Centre National de la Recherche Scientifique (CNRS), Noirhomme-Fraiture M. et Venturini G. (eds.), and Chevallier, Francois

Subjects
[INFO.INFO-AI] Computer Science [cs]/Artificial Intelligence [cs.AI], ComputingMilieux_MISCELLANEOUS, [INFO.INFO-AI]Computer Science [cs]/Artificial Intelligence [cs.AI]
Abstract

National audience

Published
2007

24. Vers une plateforme interactive pour la visualisation de grands ensembles de règles d'association

Author

Couturier, Olivier, Hamrouni, T., Ben Yahia, S., Mephu Nguifo, Engelbert, Centre de Recherche en Informatique de Lens (CRIL), Université d'Artois (UA)-Centre National de la Recherche Scientifique (CNRS), Noirhomme-Fraiture M. et Venturini G. (eds.), and Chevallier, Francois

Subjects
[INFO.INFO-AI] Computer Science [cs]/Artificial Intelligence [cs.AI], ComputingMilieux_MISCELLANEOUS, [INFO.INFO-AI]Computer Science [cs]/Artificial Intelligence [cs.AI]
Abstract

National audience

Published
2007

25. Towards a finer assessment of extraction contexts sparseness

Author

Hamrouni, T., Ben Yahia, S., Mephu Nguifo, Engelbert, Chevallier, Francois, Centre de Recherche en Informatique de Lens (CRIL), and Université d'Artois (UA)-Centre National de la Recherche Scientifique (CNRS)

Subjects
[INFO.INFO-AI] Computer Science [cs]/Artificial Intelligence [cs.AI], Computer science, business.industry, Training (meteorology), 02 engineering and technology, Variation (game tree), computer.software_genre, Distance measures, [INFO.INFO-AI]Computer Science [cs]/Artificial Intelligence [cs.AI], Identification (information), Text mining, Null (SQL), 020204 information systems, 0202 electrical engineering, electronic engineering, information engineering, 020201 artificial intelligence & image processing, Artificial intelligence, business, computer, Natural language, Natural language processing, ComputingMilieux_MISCELLANEOUS
Abstract

This paper deals with the problem of author identification. The common N-grams (CNG) method [6] is a language-independent profile-based approach with good results in many author identification experiments so far. A variation of this approach is presented based on new distance measures that are quite stable for large profile length values. Special emphasis is given to the degree upon which the effectiveness of the method is affected by the available training text samples per author. Experiments based on text samples on the same topic from the Reuters Corpus Volume 1 are presented using both balanced and imbalanced training corpora. The results show that CNG with the proposed distance measures is more accurate when only limited training text samples are available, at least for some of the candidate authors, a realistic condition in author identification problems.

Published
2007

26. Une nouvelle méthode d'alignement et de visualisation d'ontologies OWL-Lite

Author

Zghal, Sami, Kamoun, K., Ben Yahia, S., Mephu Nguifo, Engelbert, Centre de Recherche en Informatique de Lens (CRIL), Université d'Artois (UA)-Centre National de la Recherche Scientifique (CNRS), Noirhomme-Fraiture M. et Venturini G., and Chevallier, Francois

Subjects
[INFO.INFO-AI] Computer Science [cs]/Artificial Intelligence [cs.AI], ComputingMethodologies_GENERAL, ComputingMilieux_MISCELLANEOUS, [INFO.INFO-AI]Computer Science [cs]/Artificial Intelligence [cs.AI]
Abstract

Poster; National audience

Published
2007

30. EDOLA : Une nouvelle methode d'alignement d'ontologies OWL-Lite

Author

Zghal, Sami, Kamoun, K., Ben Yahia, S., Mephu Nguifo, Engelbert, Chevallier, Francois, Jean-Marie Pinon, Centre de Recherche en Informatique de Lens (CRIL), and Centre National de la Recherche Scientifique (CNRS)-Université d'Artois (UA)

Subjects
[INFO.INFO-AI] Computer Science [cs]/Artificial Intelligence [cs.AI], [INFO.INFO-AI]Computer Science [cs]/Artificial Intelligence [cs.AI]
Published
2007

31. Extraction de règles d'association à partir de données décentralisées: Problèmes et perspectives

Author

Gasmi, G., Ben Yahia, S., Mephu Nguifo, Engelbert, Centre de Recherche en Informatique de Lens (CRIL), Centre National de la Recherche Scientifique (CNRS)-Université d'Artois (UA), Boussaïd O. et Masseglia F. (eds.), and Chevallier, Francois

Subjects
[INFO.INFO-AI] Computer Science [cs]/Artificial Intelligence [cs.AI], ComputingMilieux_MISCELLANEOUS, [INFO.INFO-AI]Computer Science [cs]/Artificial Intelligence [cs.AI]
Abstract

National audience

Published
2007

32. IGB: une nouvelle base générique informative des règles d'association

Author

Gasmi, G., Ben Yahia, S., Mephu Nguifo, Engelbert, Slimani, Y., Centre de Recherche en Informatique de Lens (CRIL), Université d'Artois (UA)-Centre National de la Recherche Scientifique (CNRS), and Chevallier, Francois

Subjects
[INFO.INFO-AI] Computer Science [cs]/Artificial Intelligence [cs.AI], [INFO.INFO-AI]Computer Science [cs]/Artificial Intelligence [cs.AI]
Published
2006

33. Joint Special Issue ARIMA and SACJ: Advances in end-user data-mining techniques

Author

Ben Yahia, S., Kourie, D., Mephu Nguifo, Engelbert, Centre de Recherche en Informatique de Lens (CRIL), and Université d'Artois (UA)-Centre National de la Recherche Scientifique (CNRS)

Subjects
[INFO.INFO-AI]Computer Science [cs]/Artificial Intelligence [cs.AI]
Abstract

Proceedings{BKM-06-1

Published
2006

34. Redundancy-free Generic Bases of Association Rules

Author

Hamrouni, T., Ben Yahia, S., Mephu Nguifo, Engelbert, Centre de Recherche en Informatique de Lens (CRIL), Université d'Artois (UA)-Centre National de la Recherche Scientifique (CNRS), Miclet L., and Chevallier, Francois

Subjects
[INFO.INFO-AI] Computer Science [cs]/Artificial Intelligence [cs.AI], [INFO.INFO-AI]Computer Science [cs]/Artificial Intelligence [cs.AI]
Published
2006

35. Visualisation des règles associatives : vers une approche méta-cognitive

Author

Ben Yahia, S., Mephu Nguifo, Engelbert, Chevallier, Francois, PINON Jean Marie, Centre de Recherche en Informatique de Lens (CRIL), and Université d'Artois (UA)-Centre National de la Recherche Scientifique (CNRS)

Subjects
[INFO.INFO-AI] Computer Science [cs]/Artificial Intelligence [cs.AI], ComputingMilieux_MISCELLANEOUS, [INFO.INFO-AI]Computer Science [cs]/Artificial Intelligence [cs.AI]
Abstract

National audience

Published
2006

36. Avoiding the itemset closure computation 'pitfall'

Author

Hamrouni, T., Ben Yahia, S., Slimani, Y., Centre de Recherche en Informatique de Lens (CRIL), Université d'Artois (UA)-Centre National de la Recherche Scientifique (CNRS), and Chevallier, Francois

Subjects
[INFO.INFO-AI] Computer Science [cs]/Artificial Intelligence [cs.AI], ComputingMilieux_MISCELLANEOUS, [INFO.INFO-AI]Computer Science [cs]/Artificial Intelligence [cs.AI]
Abstract

International audience

Published
2005

37. Extracting generic basis of association rules from SAGE data

Author

Gasmi, G., Hamrouni, T., Abdelhak, S., Ben Yahia, S., Mephu Nguifo, Engelbert, Centre de Recherche en Informatique de Lens (CRIL), Université d'Artois (UA)-Centre National de la Recherche Scientifique (CNRS), and Chevallier, Francois

Subjects
[INFO.INFO-AI] Computer Science [cs]/Artificial Intelligence [cs.AI], ComputingMilieux_MISCELLANEOUS, [INFO.INFO-AI]Computer Science [cs]/Artificial Intelligence [cs.AI]
Abstract

International audience

Published
2005

38. Prince : Extraction optimisée des bases génériques de régles sans calcul de fermetures

Author

Hamrouni, T., Ben Yahia, S., Slimani, Y., Chevallier, Francois, Centre de Recherche en Informatique de Lens (CRIL), and Université d'Artois (UA)-Centre National de la Recherche Scientifique (CNRS)

Subjects
[INFO.INFO-AI] Computer Science [cs]/Artificial Intelligence [cs.AI], ComputingMilieux_MISCELLANEOUS, [INFO.INFO-AI]Computer Science [cs]/Artificial Intelligence [cs.AI]
Abstract

National audience

Published
2005

42. Query expansion using fuzzy association rules between terms

Author

Latiri-Cherif, C., Ben-Yahia, S., Chevallet, Jean-Pierre, Jaoua, A., Modélisation et Recherche d’Information Multimédia [Grenoble] (MRIM), Laboratoire d'Informatique de Grenoble (LIG), and Institut polytechnique de Grenoble - Grenoble Institute of Technology (Grenoble INP )-Institut National Polytechnique de Grenoble (INPG)-Centre National de la Recherche Scientifique (CNRS)-Université Pierre Mendès France - Grenoble 2 (UPMF)-Université Joseph Fourier - Grenoble 1 (UJF)-Institut polytechnique de Grenoble - Grenoble Institute of Technology (Grenoble INP )-Institut National Polytechnique de Grenoble (INPG)-Centre National de la Recherche Scientifique (CNRS)-Université Pierre Mendès France - Grenoble 2 (UPMF)-Université Joseph Fourier - Grenoble 1 (UJF)

Subjects
query expansion, [INFO.INFO-IR]Computer Science [cs]/Information Retrieval [cs.IR], Information Retrieval, fuzzy association rule, fuzzy Galois connection
Abstract

International audience; Information retrieval (IR) focuses on the process of determining and assessing the adequacy between a user-query and a collection of documents, yielding a subset of relevant documents. In this respect, query expansion aims to reduce an eventual query/document mismatch by expanding the query using correlated terms. In this paper, we present an approach based on the use of association rules to detect such correlations, in order to improve retrieval effectiveness by reducing such mismatch. By considering the term-document relation as a fuzzy binary relation (with a special emphasis on membership degrees semantic), we propose a fuzzy conceptual approach to extract fuzzy association rules. This approach is based on the closure of an extended fuzzy Galois connection, using different semantics of term membership degrees. An experimental study, on real textual collections, has confirmed our intuitive hypothesis that the synergy between association rules and query expansion is fruitful. Results of the study show a significant improvement in the performances of the information retrieval system, both in terms of recall and precision.

Published
2003

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