F. Dans-la, Pour chaque position i (en partant de 1) dans le U-Net, le score d'utilité de chaque candidat est calculé en utilisant l'Équation 5.8 et en prenant en compte des utilisateurs du U-Net aux positions 1, ..., i?1 ; étant donné i, si le meilleur candidat a un score d'utilité supérieur à celui de l'utilisateur U-Net u [i], alors cette étape se termine (ligne 6) Si plusieurs candidats obtiennent le meilleur score, le choix se fait de manière aléatoire. Dans la Figure 5.2, v 7 est plus utile que v 3 à la troisième position dans le U-Net car

. La-seconde-partie, déplace les profils des utilisateurs restant dans le U-Net (de la position i à N ) vers la liste des candidats (2a) ; leur 7, Conclusion Bibliographie [1] S. Abbar, S. Amer-Yahia, P. Indyk et S. Mahabadi, « Real-Time Recommendation of Diverse Related Articles », dans Proceedings of the 22nd International Conference on World Wide Web, pp.1-12, 2013.

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.734-749, 2005.
DOI : 10.1109/TKDE.2005.99

S. Amer-yahia, J. Shanmugasundaram, U. Srivastava, E. Vee, and P. Bhat, Efficient Online Computation of Diverse Query Results, p.117, 2011.

A. Anagnostopoulos, A. Z. Broder, and D. Carmel, « Sampling Search- Engine Results », World Wide Web, t, pp.397-429, 2006.

C. Anderson, The Long Tail : Why the Future of Business Is Selling Less of More. Hyperion, 2006.

M. Balabanovi?, Y. Shoham, and . Fab, Fab: content-based, collaborative recommendation, Communications of the ACM, vol.40, issue.3, pp.66-72, 1997.
DOI : 10.1145/245108.245124

E. Barnett and «. Facebook, Cuts Six Degrees of Separation to Four, 2011.

M. Bawa, G. S. Manku, P. Raghavan, and «. Sets, Search Enhanced by Topic Segmentation, dans Proceedings of the 26th Annual International ACM SIGIR Conference on Research and Development in Information Retrieval, pp.306-313, 2003.

B. H. Bloom and . Space, Space/time trade-offs in hash coding with allowable errors, Communications of the ACM, vol.13, issue.7, pp.422-426, 1970.
DOI : 10.1145/362686.362692

J. Bobadilla, F. Ortega, A. Hernando, and J. Bernal, « A Collaborative Filtering Approach to Mitigate the New User Cold Start Problem », Knowledge-Based Systems, pp.225-238, 2012.

N. Borch, « Social Peer-to-Peer for Social People, The International Conference on Internet Technologies and Applications, 2005.

Y. Busnel, A. Kermarrec, and «. Proxsem, Interest-Based Proximity Measure to Improve Search Efficiency, P2P Systems », dans European Conference on Universal Multiservice Networks, pp.62-74, 2007.
URL : https://hal.archives-ouvertes.fr/inria-00001249

S. Büttcher, C. L. Clarke, and G. V. Cormack, Information Retrieval : Implementing and Evaluating Search Engines, 2010.

J. Carbonell and J. Goldstein, The use of MMR, diversity-based reranking for reordering documents and producing summaries, Proceedings of the 21st annual international ACM SIGIR conference on Research and development in information retrieval , SIGIR '98, pp.335-336, 1998.
DOI : 10.1145/290941.291025

H. Chen and D. R. Karger, Less is more, Proceedings of the 29th annual international ACM SIGIR conference on Research and development in information retrieval , SIGIR '06, pp.429-436, 2006.
DOI : 10.1145/1148170.1148245

P. Chirita, W. Nejdl, and O. Scurtu, « Knowing Where to Search : Personalized Search Strategies for Peers in P2P Networks. », dans Workshop on Peer-to-Peer Information Retrieval, 2004.

V. Cholvi, P. Felber, and E. Biersack, Efficient search in unstructured peer-to-peer networks, European Transactions on Telecommunications, vol.10, issue.6, pp.535-548, 2004.
DOI : 10.1002/ett.1017

E. Cohen and S. Shenker, Replication strategies in unstructured peer-to-peer networks, ACM SIGCOMM Computer Communication Review, vol.32, issue.4, pp.177-190, 2002.
DOI : 10.1145/964725.633043

A. Crespo, H. Garcia-molina, and «. Routing, Indices for Peer-to-Peer Systems, Proceeding of the 22nd International Conference on Distributed Computing Systems, pp.23-32, 2002.

G. Decandia, D. Hastorun, M. Jampani, G. Kakulapati, A. Lakshman et al., Amazon's Highly Available Key-Value Store, ACM SIGOPS Operating Systems Review, pp.41-205, 2007.

M. Deshpande and G. Karypis, recommendation algorithms, ACM Transactions on Information Systems, vol.22, issue.1, pp.143-177, 2004.
DOI : 10.1145/963770.963776

R. O. Duda, P. E. Hart, and D. G. , Stork, Pattern Classification, 2012.

M. Dick, E. Pacitti, B. Kemme, and . Flower, CDN : a Hybrid P2P Overlay for Efficient Query Processing in CDN, dans Proceedings of the 12th International Conference on Extending Database Technology : Advances in Database Technology, pp.427-438, 2009.
URL : https://hal.archives-ouvertes.fr/inria-00331231

R. Fagin, A. Lotem, and M. Naor, Optimal aggregation algorithms for middleware, Proceedings of the twentieth ACM SIGMOD-SIGACT-SIGART symposium on Principles of database systems , PODS '01, pp.614-656, 2003.
DOI : 10.1145/375551.375567

A. Fast, D. Jensen, and B. N. Levine, Creating social networks to improve peer-to-peer networking, Proceeding of the eleventh ACM SIGKDD international conference on Knowledge discovery in data mining , KDD '05, pp.568-573, 2005.
DOI : 10.1145/1081870.1081938

D. Goldberg, D. Nichols, B. M. Oki, and D. Terry, Using collaborative filtering to weave an information tapestry, Communications of the ACM, vol.35, issue.12, pp.61-70, 1992.
DOI : 10.1145/138859.138867

S. Gollapudi and A. Sharma, An axiomatic approach for result diversification, Proceedings of the 18th international conference on World wide web, WWW '09, pp.381-390, 2009.
DOI : 10.1145/1526709.1526761

K. P. Gummadi, R. J. Dunn, S. Saroiu, S. D. Gribble, H. M. Levy et al., Modeling, and Analysis of a Peer-to-Peer File-Sharing Workload, ACM SIGOPS Operating Systems Review, pp.37-314, 2003.

M. M. Halldórsson, A still better performance guarantee for approximate graph coloring, Information Processing Letters, vol.45, issue.1, pp.19-23, 1993.
DOI : 10.1016/0020-0190(93)90246-6

J. Han, M. Kamber, and J. Pei, Data Mining, 2006.
DOI : 10.1007/978-1-4899-7993-3_104-2

J. Han and C. Moraga, The influence of the sigmoid function parameters on the speed of backpropagation learning, International Workshop on Artificial Neural Networks, pp.195-201, 1995.
DOI : 10.1007/3-540-59497-3_175

T. Hofmann and . Hartmann, « Collaborative Filtering with Privacy via Factor Analysis, dans Proceedings of the 2005 ACM Symposium on Applied Computing, pp.791-795, 2005.

Z. Huang, H. Chen, and D. Zeng, Applying associative retrieval techniques to alleviate the sparsity problem in collaborative filtering, ACM Transactions on Information Systems, vol.22, issue.1, pp.116-142, 2004.
DOI : 10.1145/963770.963775

A. Iamnitchi and M. , Ripeanu et I. Foster, « Locating Data in (Small- World ?) Peer-to-Peer Scientific Collaborations », dans Peer-to-Peer Systems, pp.232-241, 2002.

M. Jelasity, O. Babaoglu, and «. , Gossip-Based Overlay Topology Management », dans Engineering Self-Organising Systems, pp.1-15, 2006.

H. Jin, X. Ning, and H. Chen, Efficient search for peer-to-peer information retrieval using semantic small world, Proceedings of the 15th international conference on World Wide Web , WWW '06, pp.1003-1004, 2006.
DOI : 10.1145/1135777.1135986

V. Kalogeraki, D. Gunopulos, and D. Zeinalipour-yazti, A local search mechanism for peer-to-peer networks, Proceedings of the eleventh international conference on Information and knowledge management , CIKM '02, pp.300-307, 2002.
DOI : 10.1145/584792.584842

G. Karypis, Recommendation Algorithms, Proceedings of the tenth international conference on Information and knowledge management , CIKM'01, pp.247-254, 2001.
DOI : 10.1145/502585.502627

E. Kayaaslan, B. B. Cambazoglu, and C. Aykanat, « Document Replication Strategies for Geographically Distributed Web Search Engines », Information Processing and Management, t, pp.51-66, 2013.

A. Kermarrec and F. Taïani, Diverging towards the common good, Proceedings of the Fifth Workshop on Social Network Systems, SNS '12, p.1, 2012.
DOI : 10.1145/2181176.2181177

I. A. Klampanos and J. M. Jose, An architecture for information retrieval over semi-collaborating Peer-to-Peer networks, Proceedings of the 2004 ACM symposium on Applied computing , SAC '04, pp.1078-1083, 2004.
DOI : 10.1145/967900.968119

M. Kochen, The Small World, 1989.

G. Koutrika, B. Bercovitz, H. Garcia-molina, and «. Flexrecs, Expressing and Combining Flexible Recommendations, Proceedings of the 2009 ACM SIGMOD International Conference on Management of Data, pp.745-758, 2009.

W. Kowalczyk, M. Jelasity, and . Eiben, « Towards Data Mining in Large and Fully Distributed Peer-to-Peer Overlay Networks, Proceedings of the 15th Benelux Conference on Artificial Intelligence, pp.203-210, 2003.

K. Kummamuru, R. Lotlikar, S. Roy, K. Singal, R. Krishnapuram et al., A hierarchical monothetic document clustering algorithm for summarization and browsing search results, Proceedings of the 13th conference on World Wide Web , WWW '04, pp.658-665, 2004.
DOI : 10.1145/988672.988762

J. Li, B. T. Loo, J. M. Hellerstein, M. F. Kaashoek, D. R. Karger et al., « On the Feasibility of Peer-to-Peer Web Indexing and Search », dans Peer-to-Peer Systems II, pp.207-215, 2003.

Q. Li and B. M. Kim, An approach for combining content-based and collaborative filters, Proceedings of the sixth international workshop on Information retrieval with Asian languages -, pp.17-24, 2003.
DOI : 10.3115/1118935.1118938

G. Linden, B. Smith, J. York, and . Amazon, com Recommendations : Item-to-Item Collaborative Filtering, pp.76-80, 2003.

Q. Lv, S. Ratnasamy, and S. Shenker, « Can Heterogeneity Make Gnutella Scalable ? », dans Peer-to-Peer Systems, pp.94-103, 2002.

H. Ma, I. King, and M. R. Lyu, Effective missing data prediction for collaborative filtering, Proceedings of the 30th annual international ACM SIGIR conference on Research and development in information retrieval, SIGIR '07, pp.39-46, 2007.
DOI : 10.1145/1277741.1277751

J. Macqueen, « Some Methods for Classification and Analysis of Multivariate Observations, Proceedings of the 5th Berkeley Symposium on Mathematical Statistics and Probability, pp.281-297, 1967.

D. Malkhi, M. Naor, D. Ratajczak, and . Viceroy, A Scalable and Dynamic Emulation of the Butterfly, dans Proceedings of the Twentyfirst Annual Symposium on Principles of Distributed Computing, pp.183-192, 2002.

C. D. Manning, P. Raghavan, and H. Schütze, Introduction to Information Retrieval, 2008.
DOI : 10.1017/CBO9780511809071

P. Maymounkov, D. Mazieres, and . Kademlia, A Peer-to-Peer Information System Based on the XOR Metric », dans Peer-to-Peer Systems, pp.53-65, 2002.

S. M. Mcnee, J. Riedl, and J. A. Konstan, Being accurate is not enough, CHI '06 extended abstracts on Human factors in computing systems, CHI EA '06, pp.1097-1101, 2006.
DOI : 10.1145/1125451.1125659

D. A. Menascé and L. Kanchanapalli, Probabilistic scalable P2P resource location services, Probabilistic Scalable P2P Resource Location Services, pp.48-58, 2002.
DOI : 10.1145/588160.588167

B. N. Miller, J. A. Konstan, J. Riedl, and . Pocketlens, PocketLens, ACM Transactions on Information Systems, vol.22, issue.3, pp.437-476, 2004.
DOI : 10.1145/1010614.1010618

M. O. Connor and J. Herlocker, « Clustering Items for Collaborative Filtering, dans Proceedings of the ACM SIGIR Workshop on Recommender Systems, t. 128, 1999.

Y. Ogawa, T. Morita, and K. Kobayashi, « A Fuzzy Document Retrieval System Using the Keyword Connection Matrix and a Learning Method », Fuzzy Sets and Systems, pp.163-179, 1991.

M. T. Özsu and P. Valduriez, Principles of Distributed Database Systems, 2011.

M. Papagelis, D. Plexousakis, and T. Kutsuras, « Alleviating the Sparsity Problem of Collaborative Filtering Using Trust Inferences », dans Trust Management, pp.224-239, 2005.

M. J. Pazzani and D. Billsus, « Content-Based Recommendation Systems », dans The Adaptive Web, pp.325-341, 2007.

J. Pearl, Probabilistic Reasoning in Intelligent Systems : Networks of Plausible Inference, 1988.

J. A. Pouwelse, P. Garbacki, J. Wang, A. Bakker, J. Yang et al., Social-Based Peer-to-Peer System, Concurrency and Computation : Practice and Experience, pp.20-127, 2008.

J. R. Quinlan, Induction of decision trees, Machine Learning, pp.81-106, 1986.
DOI : 10.1007/BF00116251

S. Ratnasamy, I. Stoica, and S. Shenker, « Routing Algorithms for DHTs : Some Open Questions », dans Peer-to-Peer Systems, pp.45-52, 2002.

J. D. Rennie and N. Srebro, Fast maximum margin matrix factorization for collaborative prediction, Proceedings of the 22nd international conference on Machine learning , ICML '05, pp.713-719, 2005.
DOI : 10.1145/1102351.1102441

P. Resnick, N. Iacovou, M. Suchak, P. Bergstrom, and J. , GroupLens, Proceedings of the 1994 ACM conference on Computer supported cooperative work , CSCW '94, pp.175-186, 1994.
DOI : 10.1145/192844.192905

J. Risson and T. , Moors, « Survey of Research Towards Robust Peerto-Peer Networks : Search Methods », Computer Networks, t. 50, pp.3485-3521, 2006.

A. Rowstron, P. Druschel, and . Pastry, Pastry: Scalable, Decentralized Object Location, and Routing for Large-Scale Peer-to-Peer Systems, pp.329-350, 2001.
DOI : 10.1007/3-540-45518-3_18

O. D. Sahin, F. Emekçi, and D. Agrawal, El Abbadi, « Content- Based Similarity Search over Peer-to-Peer Systems », dans Databases, Information Systems, and Peer-to-Peer Computing, pp.61-78, 2005.

G. Salton, A. Wong, C. Yang, and «. A. , A vector space model for automatic indexing, Communications of the ACM, vol.18, issue.11, pp.613-620, 1975.
DOI : 10.1145/361219.361220

S. Saroiu, P. K. Gummadi, and S. D. Gribble, « Measurement Study of Peer-to-Peer File Sharing Systems », dans Electronic Imaging, pp.156-170, 2001.

B. M. Sarwar, G. Karypis, J. Konstan, and J. , « Recommender Systems for Large-Scale e-Commerce : Scalable Neighborhood Formation Using Clustering, Proceedings of the 5th International Conference on Computer and Information Technology, 2002.

M. Servajean, E. Pacitti, and S. , Amer-Yahia et A. El Abbadi, « Increasing Coverage in Distributed Search and Recommendation with Profile Diversity

U. Shardanand and P. Maes, Social information filtering, Proceedings of the SIGCHI conference on Human factors in computing systems, CHI '95, pp.210-217, 1995.
DOI : 10.1145/223904.223931

K. Sripanidkulchai, B. Maggs, and H. Zhang, Efficient content location using interest-based locality in peer-to-peer systems, IEEE INFOCOM 2003. Twenty-second Annual Joint Conference of the IEEE Computer and Communications Societies (IEEE Cat. No.03CH37428), pp.2166-2176, 2003.
DOI : 10.1109/INFCOM.2003.1209237

I. Stoica, R. Morris, D. Liben-nowell, D. R. Karger, M. F. Kaashoek et al., Chord: a scalable peer-to-peer lookup protocol for internet applications, IEEE/ACM Transactions on Networking, vol.11, issue.1, pp.17-32, 2003.
DOI : 10.1109/TNET.2002.808407

G. Strabon, Géographie de Strabon, grec, trad. par A. Letrone . Imprimerie Impériale, 1819.

D. Stutzbach and R. Rejaie, Understanding churn in peer-to-peer networks, Proceedings of the 6th ACM SIGCOMM on Internet measurement , IMC '06, pp.189-202, 2006.
DOI : 10.1145/1177080.1177105

C. Tang, Z. Xu, and S. Dwarkadas, Peer-to-peer information retrieval using self-organizing semantic overlay networks, Proceedings of the 2003 conference on Applications, technologies, architectures, and protocols for computer communications , SIGCOMM '03, pp.175-186, 2003.
DOI : 10.1145/863955.863976

C. Tang, Z. Xu, M. Mahalingam, and . Peersearch, Efficient Information Retrieval in Peer-to-Peer Networks, Proceedings of the 1st ACM SIGCOMM Workshop on Hot Topics in Networks, 2002.

C. Tang, Z. Xu, and M. Mahalingam, pSearch, ACM SIGCOMM Computer Communication Review, vol.33, issue.1, pp.89-94, 2003.
DOI : 10.1145/774763.774777

D. Tsoumakos and N. Roussopoulos, Adaptive probabilistic search for peer-to-peer networks, Proceedings Third International Conference on Peer-to-Peer Computing (P2P2003), pp.102-109, 2003.
DOI : 10.1109/PTP.2003.1231509

A. Tveit, Peer-to-peer based recommendations for mobile commerce, Proceedings of the 1st international workshop on Mobile commerce , WMC '01, pp.26-29, 2001.
DOI : 10.1145/381461.381466

Y. Upadrashta, J. Vassileva, and W. Grassmann, Social Networks in Peer-to-Peer Systems, Proceedings of the 38th Annual Hawaii International Conference on System Sciences, pp.200-200, 2005.
DOI : 10.1109/HICSS.2005.546

J. Verhoeff, W. Goffman, and J. Belzer, Inefficiency of the use of Boolean functions for information retrieval systems, Communications of the ACM, vol.4, issue.12, pp.557-558, 1961.
DOI : 10.1145/366853.366861

S. Voulgaris, M. Van-steen, and «. Epidemic, Epidemic-Style Management of Semantic Overlays for Content-Based Searching, Proceeding of the 2005 Euro-Par Conference on Parallel Processing, pp.1143-1152, 2005.
DOI : 10.1007/11549468_125

J. Wang, A. P. De-vries, and M. J. Reinders, Unifying user-based and item-based collaborative filtering approaches by similarity fusion, Proceedings of the 29th annual international ACM SIGIR conference on Research and development in information retrieval , SIGIR '06, pp.501-508, 2006.
DOI : 10.1145/1148170.1148257

B. Yang and H. Garcia-molina, « Efficient Search in Peer-to-Peer Networks, 2002.

B. Yang and H. Garcia-molina, Improving search in peer-to-peer networks, Proceedings 22nd International Conference on Distributed Computing Systems, pp.5-14, 2002.
DOI : 10.1109/ICDCS.2002.1022237

C. Yu and L. Lakshmanan, Amer-Yahia, « It Takes Variety to Make a World, Diversification in Recommender Systems », dans Proceedings of the 12th International Conference on Extending Database Technology : Advances in Database Technology, pp.368-378, 2009.

S. Indexation-diversifiée, 91 top-k diversifié, 34 R Recommandation Filtrage basé sur les contenus, p.20