Syst emes de recommandation sociaux et s emantiques

[1]  M. A. Beauchamp.  AN IMPROVED INDEX OF CENTRALITY. , 1965, Behavioral science.

[2]  Hsinchun Chen,et al.  A graph-based recommender system for digital library , 2002, JCDL '02.

[3]  Pattie Maes,et al.  Evolving agents for personalized information filtering , 1993, Proceedings of 9th IEEE Conference on Artificial Intelligence for Applications.

[4]  John K. Debenham,et al.  Informed Recommender: Basing Recommendations on Consumer Product Reviews , 2007, IEEE Intelligent Systems.

[5]  Alessandro Micarelli,et al.  User Profiles for Personalized Information Access , 2007, The Adaptive Web.

[6]  Jun Wang,et al.  Unifying user-based and item-based collaborative filtering approaches by similarity fusion , 2006, SIGIR.

[7]  Albert-László Barabási,et al.  Statistical mechanics of complex networks , 2001, ArXiv.

[8]  Stephen P. Borgatti,et al.  Centrality and network flow , 2005, Soc. Networks.

[9]  John Riedl,et al.  An Empirical Analysis of Design Choices in Neighborhood-Based Collaborative Filtering Algorithms , 2002, Information Retrieval.

[10]  J. Nieminen.  On the centrality in a graph. , 1974, Scandinavian journal of psychology.

[11]  Peter Mika,et al.  Social Networks and the Semantic Web , 2007, IEEE/WIC/ACM International Conference on Web Intelligence (WI'04).

[12]  J. Moody.  Race, School Integration, and Friendship Segregation in America1 , 2001, American Journal of Sociology.

[13]  Anne Boyer,et al.  A Client/Server User-Based Collaborative Filtering Algorithm: Model and Implementation , 2006, ECAI.

[14]  Henry Lieberman,et al.  Letizia: An Agent That Assists Web Browsing , 1995, IJCAI.

[15]  Stuart A. Rice,et al.  The Identification of Blocs in Small Political Bodies , 1927, American Political Science Review.

[16]  James Bennett,et al.  The Netflix Prize , 2007 .

[17]  Bradley N. Miller,et al.  Using filtering agents to improve prediction quality in the GroupLens research collaborative filtering system , 1998, CSCW '98.

[18]  Brian W. Kernighan,et al.  An efficient heuristic procedure for partitioning graphs , 1970, Bell Syst. Tech. J..

[19]  Carlo Strapparava,et al.  Improving User Modelling with Content-Based Techniques , 2001, User Modeling.

[20]  Douglas B. Terry,et al.  Using collaborative filtering to weave an information tapestry , 1992, CACM.

[21]  Bradley N. Miller,et al.  MovieLens unplugged: experiences with an occasionally connected recommender system , 2003, IUI '03.

[22]  John Riedl,et al.  Analysis of recommendation algorithms for e-commerce , 2000, EC '00.

[23]  Hsinchun Chen,et al.  Applying associative retrieval techniques to alleviate the sparsity problem in collaborative filtering , 2004, TOIS.

[24]  Jure Leskovec,et al.  Predicting positive and negative links in online social networks , 2010, WWW '10.

[25]  Wenliang Du,et al.  Privacy-preserving collaborative filtering using randomized perturbation techniques , 2003, Third IEEE International Conference on Data Mining.

[26]  Jelena Grujic,et al.  Movies Recommendation Networks as Bipartite Graphs , 2008, ICCS.

[27]  Robert E. Tarjan,et al.  Depth-First Search and Linear Graph Algorithms , 1972, SIAM J. Comput..

[28]  Sergey Brin,et al.  The Anatomy of a Large-Scale Hypertextual Web Search Engine , 1998, Comput. Networks.

[29]  Leo Katz,et al.  A new status index derived from sociometric analysis , 1953 .

[30]  G. A. Miller.  THE PSYCHOLOGICAL REVIEW THE MAGICAL NUMBER SEVEN, PLUS OR MINUS TWO: SOME LIMITS ON OUR CAPACITY FOR PROCESSING INFORMATION 1 , 1956 .

[31]  Xin-She Yang,et al.  Introduction to Algorithms , 2021, Nature-Inspired Optimization Algorithms.

[32]  Andreas Hotho,et al.  FolkRank : A Ranking Algorithm for Folksonomies , 2006, LWA.

[33]  Dorothea Wagner,et al.  Approximating Clustering Coefficient and Transitivity , 2005, J. Graph Algorithms Appl..

[34]  Iraklis Varlamis,et al.  SEWeP: using site semantics and a taxonomy to enhance the Web personalization process , 2003, KDD '03.

[35]  Mark S. Granovetter.  The Strength of Weak Ties , 1973, American Journal of Sociology.

[36]  Lada A. Adamic,et al.  Search in Power-Law Networks , 2001, Physical review. E, Statistical, nonlinear, and soft matter physics.

[37]  Albert-László Barabási,et al.  Internet: Diameter of the World-Wide Web , 1999, Nature.

[38]  Michael J. Pazzani,et al.  Learning Collaborative Information Filters , 1998, ICML.

[39]  Jonathan L. Herlocker,et al.  Evaluating collaborative filtering recommender systems , 2004, TOIS.

[40]  M. Newman,et al.  Scientific collaboration networks. II. Shortest paths, weighted networks, and centrality. , 2001, Physical review. E, Statistical, nonlinear, and soft matter physics.

[41]  D. Sade,et al.  Sociometrics of Macaca Mulatta III: n-path centrality in grooming networks , 1989 .

[42]  José Juan Pazos-Arias,et al.  Providing entertainment by content-based filtering and semantic reasoning in intelligent recommender systems , 2008, IEEE Transactions on Consumer Electronics.

[43]  Boi Faltings,et al.  OSS: A Semantic Similarity Function based on Hierarchical Ontologies , 2007, IJCAI.

[44]  Marco Gori,et al.  ItemRank: A Random-Walk Based Scoring Algorithm for Recommender Engines , 2007, IJCAI.

[45]  David Heckerman,et al.  Empirical Analysis of Predictive Algorithms for Collaborative Filtering , 1998, UAI.

[46]  Greg Linden,et al.  Amazon . com Recommendations Item-to-Item Collaborative Filtering , 2001 .

[47]  Sean M. McNee,et al.  Getting to know you: learning new user preferences in recommender systems , 2002, IUI '02.

[48]  Lars Schmidt-Thieme,et al.  Taxonomy-driven computation of product recommendations , 2004, CIKM '04.

[49]  Phillip Bonacich,et al.  Some unique properties of eigenvector centrality , 2007, Soc. Networks.

[50]  M E J Newman,et al.  Fast algorithm for detecting community structure in networks. , 2003, Physical review. E, Statistical, nonlinear, and soft matter physics.

[51]  David M. Pennock,et al.  Categories and Subject Descriptors , 2001 .

[52]  Jean-Loup Guillaume,et al.  Fast unfolding of communities in large networks , 2008, 0803.0476.

[53]  Michael J. Pazzani,et al.  User Modeling for Adaptive News Access , 2000, User Modeling and User-Adapted Interaction.

[54]  Jon Kleinberg,et al.  The link prediction problem for social networks , 2003, CIKM '03.

[55]  Òscar Celma,et al.  Foafing the Music: A Music Recommendation System based on RSS Feeds and User Preferences , 2005, ISMIR.

[56]  Michael J. Pazzani,et al.  A hybrid user model for news story classification , 1999 .

[57]  David D. Jensen,et al.  Graph clustering with network structure indices , 2007, ICML '07.

[58]  Jon Kleinberg,et al.  Authoritative sources in a hyperlinked environment , 1999, SODA '98.

[59]  Donald E. Knuth,et al.  The Stanford GraphBase - a platform for combinatorial computing , 1993 .

[60]  D. Bu,et al.  Topological structure analysis of the protein-protein interaction network in budding yeast. , 2003, Nucleic acids research.

[61]  Martin Ester,et al.  TrustWalker: a random walk model for combining trust-based and item-based recommendation , 2009, KDD.

[62]  Munindar P. Singh,et al.  Searching social networks , 2003, AAMAS '03.

[63]  Mark S. Ackerman,et al.  Searching for expertise in social networks: a simulation of potential strategies , 2005, GROUP.

[64]  François Fouss,et al.  A novel way of computing similarities between nodes of a graph, with application to collaborative recommendation , 2005, The 2005 IEEE/WIC/ACM International Conference on Web Intelligence (WI'05).

[65]  Michael J. Pazzani,et al.  Syskill & Webert: Identifying Interesting Web Sites , 1996, AAAI/IAAI, Vol. 1.

[66]  Philip Resnik,et al.  Using Information Content to Evaluate Semantic Similarity in a Taxonomy , 1995, IJCAI.

[67]  Thomas R. Gruber,et al.  A translation approach to portable ontology specifications , 1993 .

[68]  John A. Tomlin,et al.  A new paradigm for ranking pages on the world wide web , 2003, WWW '03.

[69]  R. Weiss,et al.  A Method for the Analysis of the Structure of Complex Organizations , 1955 .

[70]  Christiane Fellbaum,et al.  Combining Local Context and Wordnet Similarity for Word Sense Identification , 1998 .

[71]  U. Brandes.  A faster algorithm for betweenness centrality , 2001 .

[72]  Upendra Shardanand.  Social information filtering for music recommendation , 1994 .

[73]  M. Newman.  1 Who is the best connected scientist ? A study of scientific coauthorship networks , 2004 .

[74]  Peter Norvig,et al.  Artificial Intelligence: A Modern Approach , 1995 .

[75]  John Riedl,et al.  Item-based collaborative filtering recommendation algorithms , 2001, WWW '01.

[76]  Robin D. Burke,et al.  Hybrid Recommender Systems: Survey and Experiments , 2002, User Modeling and User-Adapted Interaction.

[77]  Rajeev Motwani,et al.  The PageRank Citation Ranking : Bringing Order to the Web , 1999, WWW 1999.

[78]  M E J Newman,et al.  Community structure in social and biological networks , 2001, Proceedings of the National Academy of Sciences of the United States of America.

[79]  Allan Borodin,et al.  Link analysis ranking: algorithms, theory, and experiments , 2005, TOIT.

[80]  Dunja Mladenic,et al.  kNN Versus SVM in the Collaborative Filtering Framework , 2006, Data Science and Classification.

[81]  Jitendra Malik,et al.  Normalized cuts and image segmentation , 1997, Proceedings of IEEE Computer Society Conference on Computer Vision and Pattern Recognition.

[82]  W. Zachary,et al.  An Information Flow Model for Conflict and Fission in Small Groups , 1977, Journal of Anthropological Research.

[83]  Matthew Richardson,et al.  The Intelligent surfer: Probabilistic Combination of Link and Content Information in PageRank , 2001, NIPS.

[84]  Trevor Hastie,et al.  The Elements of Statistical Learning , 2001 .

[85]  Bruce Krulwich,et al.  The InfoFinder Agent: Learning User Interests through Heuristic Phrase Extraction , 1997, IEEE Expert.

[86]  Céline Rouveirol,et al.  A supervised machine learning link prediction approach for academic collaboration recommendation , 2010, RecSys '10.

[87]  Charles Kadushin,et al.  The Intersection of Social Circles , 1976 .

[88]  Thomas Hofmann,et al.  Collaborative filtering via gaussian probabilistic latent semantic analysis , 2003, SIGIR.

[89]  Geoffrey E. Hinton,et al.  Restricted Boltzmann machines for collaborative filtering , 2007, ICML '07.

[90]  Paul Resnick,et al.  Recommender systems , 1997, CACM.

[91]  Lior Rokach,et al.  Introduction to Recommender Systems Handbook , 2011, Recommender Systems Handbook.

[92]  Marc Boullé,et al.  Comparing State-of-the-Art Collaborative Filtering Systems , 2007, MLDM.

[93]  Pattie Maes,et al.  Social information filtering: algorithms for automating “word of mouth” , 1995, CHI '95.

[94]  Frank Harary,et al.  Graph Theory , 2016 .

[95]  Jure Leskovec,et al.  Discovering social circles in ego networks , 2012, ACM Trans. Knowl. Discov. Data.

[96]  Fabio Crestani,et al.  Searching the web by constrained spreading activation , 2000, Inf. Process. Manag..

[97]  Noah E. Friedkin,et al.  Theoretical Foundations for Centrality Measures , 1991, American Journal of Sociology.

[98]  Michael J. Pazzani,et al.  A Framework for Collaborative, Content-Based and Demographic Filtering , 1999, Artificial Intelligence Review.

[99]  Larry Kerschberg,et al.  A semantic taxonomy-based personalizable meta-search agent , 2001, Proceedings of the Second International Conference on Web Information Systems Engineering.

[100]  Alan F. Smeaton,et al.  Improving the Quality of the Personalized Electronic Program Guide , 2004, User Modeling and User-Adapted Interaction.

[101]  John Riedl,et al.  GroupLens: an open architecture for collaborative filtering of netnews , 1994, CSCW '94.

[102]  Dekang Lin,et al.  An Information-Theoretic Definition of Similarity , 1998, ICML.

[103]  Naren Ramakrishnan,et al.  Studying Recommendation Algorithms by Graph Analysis , 2003, Journal of Intelligent Information Systems.

[104]  Stanley Milgram,et al.  An Experimental Study of the Small World Problem , 1969 .

[105]  Abhinandan Das,et al.  Google news personalization: scalable online collaborative filtering , 2007, WWW '07.

[106]  P. Bonacich.  Power and Centrality: A Family of Measures , 1987, American Journal of Sociology.

[107]  George Karypis,et al.  A Comprehensive Survey of Neighborhood-based Recommendation Methods , 2011, Recommender Systems Handbook.

[108]  Ravi Kumar,et al.  Structure and evolution of online social networks , 2006, KDD '06.

[109]  K. Sneppen,et al.  Specificity and Stability in Topology of Protein Networks , 2002, Science.

[110]  Mark Newman,et al.  Networks: An Introduction , 2010 .

[111]  George Karypis,et al.  Item-based top-N recommendation algorithms , 2004, TOIS.

[112]  Irena Koprinska,et al.  INTIMATE: a Web-based movie recommender using text categorization , 2003, Proceedings IEEE/WIC International Conference on Web Intelligence (WI 2003).

[113]  Sergio A. Alvarez,et al.  Efficient Adaptive-Support Association Rule Mining for Recommender Systems , 2004, Data Mining and Knowledge Discovery.

[114]  Yi Zhang,et al.  Graph-based ranking algorithms for e-mail expertise analysis , 2003, DMKD '03.

[115]  Antti Autere.  Aas an Optimal Resource Allocation Policy in Path Finding Problems , 2001, FLAIRS Conference.

[116]  Jure Leskovec,et al.  Supervised random walks: predicting and recommending links in social networks , 2010, WSDM '11.

[117]  Mark S. Ackerman,et al.  Expertise recommender: a flexible recommendation system and architecture , 2000, CSCW '00.

[118]  Yu He,et al.  The YouTube video recommendation system , 2010, RecSys '10.

[119]  Ulrike von Luxburg,et al.  A tutorial on spectral clustering , 2007, Stat. Comput..

[120]  J. C. Dunn,et al.  A Fuzzy Relative of the ISODATA Process and Its Use in Detecting Compact Well-Separated Clusters , 1973 .

[121]  Nils J. Nilsson,et al.  A Formal Basis for the Heuristic Determination of Minimum Cost Paths , 1968, IEEE Trans. Syst. Sci. Cybern..

[122]  Mark E. J. Newman,et al.  The Structure and Function of Complex Networks , 2003, SIAM Rev..

[123]  M E J Newman,et al.  Finding and evaluating community structure in networks. , 2003, Physical review. E, Statistical, nonlinear, and soft matter physics.

[124]  Christos Faloutsos,et al.  Graphs over time: densification laws, shrinking diameters and possible explanations , 2005, KDD '05.

[125]  S. N. Dorogovtsev,et al.  Self-organization of collaboration networks. , 2004, Physical review. E, Statistical, nonlinear, and soft matter physics.

[126]  M. Zelen,et al.  Rethinking centrality: Methods and examples☆ , 1989 .

[127]  Jon M Kleinberg,et al.  Hubs, authorities, and communities , 1999, CSUR.

[128]  Stuart E. Middleton,et al.  Ontological user profiling in recommender systems , 2004, TOIS.

[129]  Pablo Castells,et al.  Enriching Group Profiles with Ontologies for Knowledge-Driven Colalborative Content Retrieval , 2006, 15th IEEE International Workshops on Enabling Technologies: Infrastructure for Collaborative Enterprises (WETICE'06).

[130]  M. Newman,et al.  Finding community structure in networks using the eigenvectors of matrices. , 2006, Physical review. E, Statistical, nonlinear, and soft matter physics.

[131]  Jirí Síma,et al.  On the NP-Completeness of Some Graph Cluster Measures , 2005, SOFSEM.

[132]  Pavel Berkhin,et al.  A Survey on PageRank Computing , 2005, Internet Math..

[133]  Jure Leskovec,et al.  The dynamics of viral marketing , 2005, EC '06.

[134]  Tao Luo,et al.  Effective personalization based on association rule discovery from web usage data , 2001, WIDM '01.

[135]  C. Lee Giles,et al.  CiteSeer: an autonomous Web agent for automatic retrieval and identification of interesting publications , 1998, AGENTS '98.

[136]  Mark S. Ackerman,et al.  Expertise networks in online communities: structure and algorithms , 2007, WWW '07.

[137]  Sangkeun Lee,et al.  Random walk based entity ranking on graph for multidimensional recommendation , 2011, RecSys '11.

[138]  Gediminas Adomavicius,et al.  Toward the next generation of recommender systems: a survey of the state-of-the-art and possible extensions , 2005, IEEE Transactions on Knowledge and Data Engineering.

[139]  Michael I. Jordan,et al.  Stable algorithms for link analysis , 2001, SIGIR '01.

[140]  Yehuda Koren,et al.  Lessons from the Netflix prize challenge , 2007, SKDD.

[141]  Sangkeun Lee,et al.  Flexible recommendation using random walks on implicit feedback graph , 2011, ICUIMC '11.

[142]  John Riedl,et al.  Application of Dimensionality Reduction in Recommender System - A Case Study , 2000 .

[143]  Thomas R. Gruber,et al.  Toward principles for the design of ontologies used for knowledge sharing? , 1995, Int. J. Hum. Comput. Stud..

[144]  J. MacQueen.  Some methods for classification and analysis of multivariate observations , 1967 .

[145]  Jennifer Widom,et al.  Scaling personalized web search , 2003, WWW '03.

[146]  Takeo Kanade,et al.  Maximum Entropy for Collaborative Filtering , 2004, UAI.

[147]  Yehuda Koren,et al.  Factorization meets the neighborhood: a multifaceted collaborative filtering model , 2008, KDD.

[148]  Santo Fortunato,et al.  Community detection in graphs , 2009, ArXiv.

[149]  Yehuda Koren,et al.  Modeling relationships at multiple scales to improve accuracy of large recommender systems , 2007, KDD '07.

[150]  Philip Resnik,et al.  Semantic Similarity in a Taxonomy: An Information-Based Measure and its Application to Problems of Ambiguity in Natural Language , 1999, J. Artif. Intell. Res..

[151]  Peter Brusilovsky,et al.  Open user profiles for adaptive news systems: help or harm? , 2007, WWW '07.

[152]  Yoav Shoham,et al.  Fab: content-based, collaborative recommendation , 1997, CACM.

[153]  Lada A. Adamic,et al.  How to search a social network , 2005, Soc. Networks.

[154]  L. Freeman.  Centrality in social networks conceptual clarification , 1978 .

[155]  Jacob L. Moreno,et al.  Who shall survive? : foundations of sociometry, group psychotherapy, and sociodrama , 1953 .

[156]  Xavier Serra,et al.  FOAFing the music: Bridging the semantic gap in music recommendation , 2008, J. Web Semant..

[157]  George A. Miller,et al.  Introduction to WordNet: An On-line Lexical Database , 1990 .

[158]  R. Bhatia.  Matrix Analysis , 1996 .

[159]  Richard E. Korf,et al.  Depth-First Iterative-Deepening: An Optimal Admissible Tree Search , 1985, Artif. Intell..

[160]  Mark E. J. Newman.  A measure of betweenness centrality based on random walks , 2005, Soc. Networks.

[161]  Markus Koppenberger,et al.  Topology of music recommendation networks. , 2006, Chaos.

[162]  Philip S. Yu,et al.  Horting hatches an egg: a new graph-theoretic approach to collaborative filtering , 1999, KDD '99.

[163]  Bradley N. Miller,et al.  GroupLens: applying collaborative filtering to Usenet news , 1997, CACM.

[164]  James A. Hendler,et al.  Inferring binary trust relationships in Web-based social networks , 2006, TOIT.

[165]  Dominique Laurent,et al.  Graph Searching Algorithms for Semantic-Social Recommendation , 2012, 2012 IEEE/ACM International Conference on Advances in Social Networks Analysis and Mining.

[166]  Jon M. Kleinberg,et al.  Automatic Resource Compilation by Analyzing Hyperlink Structure and Associated Text , 1998, Comput. Networks.

[167]  Yi-Cheng Zhang,et al.  Bipartite network projection and personal recommendation. , 2007, Physical review. E, Statistical, nonlinear, and soft matter physics.

[168]  Taghi M. Khoshgoftaar,et al.  A Survey of Collaborative Filtering Techniques , 2009, Adv. Artif. Intell..

[169]  Kristen Grauman,et al.  Semantic Kernel Forests from Multiple Taxonomies , 2012, NIPS.

[170]  M E Newman,et al.  Scientific collaboration networks. I. Network construction and fundamental results. , 2001, Physical review. E, Statistical, nonlinear, and soft matter physics.

[171]  Loriene Roy,et al.  Content-based book recommending using learning for text categorization , 1999, DL '00.

[172]  Raymond J. Mooney and Paul N. Bennett and Loriene Roy,et al.  Book Recommending Using Text Categorization with Extracted Information , 1998 .

[173]  L. Freeman,et al.  Centrality in valued graphs: A measure of betweenness based on network flow , 1991 .

[174]  Pasquale Lops,et al.  Content-based Recommender Systems: State of the Art and Trends , 2011, Recommender Systems Handbook.

[175]  Roger V. Gould,et al.  Structures of Mediation: A Formal Approach to Brokerage in Transaction Networks , 1989 .

[176]  Sangkeun Lee.  A generic graph-based multidimensional recommendation framework and its implementations , 2012, WWW.

[177]  Michael J. Pazzani,et al.  Learning and Revising User Profiles: The Identification of Interesting Web Sites , 1997, Machine Learning.

[178]  Hans-Peter Kriegel,et al.  Ieee Transactions on Knowledge and Data Engineering Probabilistic Memory-based Collaborative Filtering , 2022 .

[179]  Marko Balabanovic,et al.  Exploring Versus Exploiting when Learning User Models for Text Recommendation , 2004, User Modeling and User-Adapted Interaction.