Automated user modeling for personalized digital libraries
暂无分享,去创建一个
Enrique Frías-Martínez | Sherry Y. Chen | Robert D. Macredie | George D. Magoulas | E. Frías-Martínez | G. Magoulas | R. Macredie | Sherry Y. Chen
[1] Peter Brusilovsky,et al. User as Student: Towards an Adaptive Interface for Advanced Web-Based Applications , 1997 .
[2] Xiangmin Zhang. Discriminant Analysis as a Machine Learning Method for Revision of User Stereotypes of Information Retrieval Systems , 2003 .
[3] Andreas Rauber,et al. SOMLib: a digital library system based on neural networks , 1999, DL '99.
[4] Jirí Materna. Automatic Web Page Classification , 2008, RASLAN.
[5] Josep Lluís de la Rosa i Esteva,et al. A Taxonomy of Recommender Agents on the Internet , 2003, Artificial Intelligence Review.
[6] Ian H. Witten,et al. Data mining: practical machine learning tools and techniques, 3rd Edition , 1999 .
[7] P. Langley,et al. Average-case analysis of a nearest neighbor algorthim , 1993, IJCAI 1993.
[8] C. Lee Giles,et al. A system for automatic personalized tracking of scientific literature on the Web , 1999, DL '99.
[9] Fabio Abbattista,et al. Learning Interaction Models in a Digital Library Service , 2001, User Modeling.
[10] David L. Hicks,et al. Towards Support for Personalization in Distributed Digital Library Settings , 2001, DELOS.
[11] Luigi Palopoli,et al. On the Complexity of Mining Association Rules , 2001, SEBD.
[12] Ramesh R. Sarukkai,et al. Link prediction and path analysis using Markov chains , 2000, Comput. Networks.
[13] Forest Baskett,et al. An Algorithm for Finding Nearest Neighbors , 1975, IEEE Transactions on Computers.
[14] Judy Kay,et al. Proceedings of the seventh international conference on User modeling , 1999 .
[15] Yannis Manolopoulos,et al. . EFFECTIVE PREDICTION OF WEB-USER ACCESSES: A DATA MINING APPROACH , 2001 .
[16] Doug Riecken,et al. Introduction: personalized views of personalization , 2000, CACM.
[17] Camino Fernández,et al. WAY : A user adapted access to information , 2005 .
[18] Fabio Abbattista,et al. Intelligent Information Retrieval in a Digital Library Service , 2000, DELOS.
[19] Alfred Kobsa,et al. Adaptable and Adaptive Information Access for All Users, Including the Disabled and the Elderly , 1997 .
[20] Eric Horvitz,et al. The Lumière Project: Bayesian User Modeling for Inferring the Goals and Needs of Software Users , 1998, UAI.
[21] James C. Bezdek,et al. Pattern Recognition with Fuzzy Objective Function Algorithms , 1981, Advanced Applications in Pattern Recognition.
[22] Anupam Joshi,et al. Low-complexity fuzzy relational clustering algorithms for Web mining , 2001, IEEE Trans. Fuzzy Syst..
[23] Ian Witten,et al. Data Mining , 2000 .
[24] Ian H. Witten,et al. Data mining: practical machine learning tools and techniques with Java implementations , 2002, SGMD.
[25] Vincent Kanade,et al. Clustering Algorithms , 2021, Wireless RF Energy Transfer in the Massive IoT Era.
[26] Dustin Boswell,et al. Introduction to Support Vector Machines , 2002 .
[27] Nigel Ford,et al. Individual differences, hypermedia navigation, and learning: an empirical study , 2000 .
[28] B. Cornelis. Personalizing search in digital libraries , 2003 .
[29] Ingrid Zukerman,et al. Predicting users' requests on the WWW , 1999 .
[30] George Buchanan,et al. Design Guidelines and User-Centred Digital Libraries , 1999, ECDL.
[31] Dwi H. Widyantoro,et al. Dynamic modeling and learning user profile in personalized news agent , 1999 .
[32] Jean-David Ruvini. Adapting to the User's Internet Search Strategy , 2003, User Modeling.
[33] Geoffrey I. Webb,et al. # 2001 Kluwer Academic Publishers. Printed in the Netherlands. Machine Learning for User Modeling , 1999 .
[34] Tomasz Imielinski,et al. Mining association rules between sets of items in large databases , 1993, SIGMOD Conference.
[35] Teuvo Kohonen,et al. Self-Organizing Maps , 2010 .
[36] Ronald L. Rivest,et al. Training a 3-node neural network is NP-complete , 1988, COLT '88.
[37] George D. Magoulas,et al. Adaptive web-based learning: accommodating individual differences through system's adaptation , 2003, Br. J. Educ. Technol..
[38] Umberto Straccia,et al. The Personalized, Collaborative Digital Library Environment CYCLADES and Its Collections Management , 2003, Distributed Multimedia Information Retrieval.
[39] Michael J. Pazzani,et al. A hybrid user model for news story classification , 1999 .
[40] Nicola Fanizzi,et al. An adaptive visual environment for digital libraries , 1999, International Journal on Digital Libraries.
[41] Constantine D. Spyropoulos,et al. Exploiting learning techniques for the acquisition of user stereotypes and communities , 1999 .
[42] Jean-David Ruvini. Adapting to the user's internet search strategy on small devices , 2003, IUI '03.
[43] Finn V. Jensen,et al. Bayesian Networks and Decision Graphs , 2001, Statistics for Engineering and Information Science.
[44] Alfred Kobsa,et al. Generic User Modeling Systems , 2001, User Modeling and User-Adapted Interaction.
[45] Alex Bateman,et al. An introduction to hidden Markov models. , 2007, Current protocols in bioinformatics.
[46] Vasileios Hatzivassiloglou,et al. Leveraging a common representation for personalized search and summarization in a medical digital library , 2003, 2003 Joint Conference on Digital Libraries, 2003. Proceedings..
[47] Atsuhiro Takasu,et al. Category Based Customization Approach for Information Retrieval , 2001, User Modeling.
[48] Daniel S. Hirschberg,et al. The Time Complexity of Decision Tree Induction , 1995 .
[49] Takashi Washio,et al. Automatic Web-Page Classification by Using Machine Learning Methods , 2001, Web Intelligence.
[50] Ken Winter. MyLibrary can help your library , 1999 .
[51] Michael A. Shepherd,et al. Adaptive user modeling for filtering electronic news , 2002, Proceedings of the 35th Annual Hawaii International Conference on System Sciences.
[52] Bin Zhu,et al. A Collection of Visual Thesauri for Browsing Large Collections of Geographic Images , 1999, J. Am. Soc. Inf. Sci..
[53] Anil K. Jain,et al. Algorithms for Clustering Data , 1988 .
[54] Alan F. Smeaton,et al. Personalisation and recommender systems in digital libraries , 2005, International Journal on Digital Libraries.
[55] Ian Davidson,et al. Speeding up k-means Clustering by Bootstrap Averaging , 2003 .
[56] Udi Manber,et al. Experience with personalization of Yahoo! , 2000, CACM.
[57] Pat Langley,et al. Average-Case Analysis of a Nearest Neighbor Algorithm , 1993, IJCAI.
[58] David A. Tyckoson. What's Right with Reference. , 1999 .
[59] Jos van Hillegersberg,et al. Enterprise resource planning: ERP adoption by European midsize companies , 2000, CACM.
[60] Robert Meersman,et al. On the Complexity of Mining Quantitative Association Rules , 1998, Data Mining and Knowledge Discovery.
[61] Ali Zilouchian,et al. FUNDAMENTALS OF NEURAL NETWORKS , 2001 .
[62] D. Lindley. Bayes theory , 1984 .
[63] J. MacQueen. Some methods for classification and analysis of multivariate observations , 1967 .
[64] K. Priyantha. PERSONALIZATION TOOLS FOR ACTIVE LEARNING IN DIGITAL LIBRARIES by Champa Jayawardana, K. Priyantha Hewagamage and Masahito Hirakawa, Database Systems , 2001 .
[65] Yiming Yang,et al. Intelligent information retrieval , 1999, IEEE Intelligent Systems and their Applications.
[66] Johan Bollen,et al. MyLibrary, A Personalization Service for Digital Library Environments , 2001, DELOS.
[67] Holly Mistlebauer,et al. MyLibrary: Personalized Electronic Services in the Cornell University Library , 2000, D Lib Mag..
[68] Nicholas J. Belkin,et al. Information filtering and information retrieval: two sides of the same coin? , 1992, CACM.