Bibliography
- [agrawal93mining] Rakesh
Agrawal, Tomasz Imielinski, and Arun N. Swami.
Mining Association
Rules between Sets of Items in Large Databases.
In Peter Buneman and Sushil Jajodia, editors, Proceedings of the 1993
ACM SIGMOD International Conference on Management of Data, pages
207–216, Washington, D.C., 1993.
- [amari80topographic] Shun-Ichi Amari.
Topographic Organization of Nerve Fields.
Bulletin of Mathematical Biology, 42:339–364, 1980.
- [anderson04wired] Chris Anderson.
The Long
Tail.
Wired, 12(10), October 2004.
- [arbib03handbook] Michael A. Arbib.
Part I: Background: The Elements of Brain Theory and Neural
Networks.
In Michael A. Arbib, editor, The Handbook of Brain Theory and
Neural Networks, pages 3–23. The MIT Press, 2 edition, 2003.
- [baeza-yates99modern] Ricardo A. Baeza-Yates and Berthier Ribeiro-Neto.
Modern Information Retrieval.
Addison-Wesley Longman Publishing Co., Inc., Boston, MA, USA, 1999.
- [balabanovic97fab] Marko
Balabanovic and Yoav Shoham.
Fab:
Content-Based, Collaborative Recommendation.
Communications of the ACM, 40(3):66–72, March 1997.
(doi:10.1145/245108.245124)
- [basu98recommendation] Chumki Basu,
Haym Hirsh, and William W. Cohen.
Recommendation as
Classification: Using Social and Content-Based Information in
Recommendation.
In AAAI '98/IAAI '98: Proceedings of the fifteenth national/tenth
conference on Artificial intelligence/Innovative applications of artificial
intelligence, pages 714–720, Menlo Park, CA, USA, 1998. American
Association for Artificial Intelligence.
- [belkin92information] Nicholas J. Belkin and W. Bruce Croft.
Information Filtering and Information Retrieval: Two Sides of the
Same Coin?
Communications of the ACM, 35(12):29–38, 1992.
(doi:10.1145/138859.138861)
- [bilgic05explaining] Mustafa
Bilgic and Raymond J. Mooney.
Explaining Recommendations: Satisfaction vs. Promotion.
In Proceedings of Beyond Personalization 2005, the Workshop on the Next
Stage of Recommender Systems Research(IUI2005), San Diego, California,
January 2005.
- [billsus98learning] Daniel
Billsus and Michael J. Pazzani.
Learning Collaborative Information Filters.
In Proceedings of the Fifteenth International Conference on Machine
Learning, pages 46–54. Morgan Kaufmann, San Francisco, CA, 1998.
- [breese98empirical] John S.
Breese, David Heckerman, and Carl Kadie.
Empirical Analysis of Predictive Algorithms for Collaborative
Filtering.
In Proceedings of the 14th Annual Conference on Uncertainty in Artificial
Intelligence (UAI-98), pages 43–52. Morgan Kaufmann, 1998.
- [brin98anatomy] Sergey Brin and
Lawrence Page.
The anatomy of a large-scale hypertextual Web search engine.
Computer Networks and ISDN Systems, 30(1–7):107–117, 1998.
- [burke02hybrid] Robin Burke.
Hybrid Recommender Systems: Survey and Experiments.
User Modeling and User-Adapted Interaction, 12(4):331–370, 2002.
(doi:10.1023/A:1021240730564)
- [carpenter89neural] G.A. Carpenter.
Neural Network Models for Pattern Recognition and Associative
Memory.
Neural Networks, 2(4):243–257, 1989.
(doi:10.1016/0893-6080(89)90035-X)
- [claypool99combining] M. Claypool, A. Gokhale, T. Miranda, P. Murnikov, D. Netes,
and M. Sartin.
Combining
Content-Based and Collaborative Filters in an Online
Newspaper.
In Proceedings of ACM SIGIR Workshop on Recommender Systems,
August 1999.
- [cacm92communications] Jacques Cohen,
editor.
Communications of the ACM. Special issue on information
filtering., volume 35, New York, NY, USA, December 1992. ACM Press.
- [oconner99clustering] M. O. Conner and J. Herlocker.
Clustering Items for Collaborative Filtering.
In Proceedings of the ACM SIGIR Workshop on Recommender
Systems, 1999.
- [cottrell98theoretical] Marie
Cottrell, Jean-Claude Fort, and Gilles Pagès.
Theoretical aspects
of the SOM algorithm..
Neurocomputing, 21(1–3):119–138, 1998.
- [cacm97communications] Diane Crawford,
editor.
Communications of the ACM, volume 40, New York, NY, USA, March
1997. ACM Press.
- [denning82electronic] Peter J. Denning.
ACM President's Letter: Electronic Junk.
Communications of the ACM, 25(3):163–165, 1982.
(doi:10.1145/358453.358454)
- [karypis04itembased] Mukund Deshpande and George Karypis.
Item-Based Top-N Recommendation Algorithms.
ACM Transactions on Information Systems, 22(1):143–177, 2004.
- [erwin92ordering] E. Erwin,
K. Obermayer, and K. J. Schulten.
Self-Organizing Maps: Ordering,
Convergence Properties and Energy Functions.
Biological Cybernetics, 67:47–55, 1992.
- [fleischman03recommendations] M. Fleischman and Eduard Hovy.
Recommendations Without User Preferences: A Natural
Language Processing Approach.
In Proceedings of the 7th International Conference on Intelligent User
Interfaces (IUI). Miami Beach, FL., 2003.
- [flexer97limitations] A. Flexer.
Limitations of
Self-Organizing Maps for Vector Quantization and Multidimensional
Scaling.
In M. C. Mozer, M. I. Jordan, and T. Petsche, editors, Advances in Neural
Information Processing Systems 9. Proceedings of the 1996 Conference,
pages 445–51. MIT Press, London, UK, 1997.
- [fukushima75cognitron] K. Fukushima.
Cognitron: A Self-Organizing Multilayered Neural Network.
Biological Cybernetics, 20:121–136, 1975.
- [fukushima80neocognitron] K. Fukushima.
Neocognitron: A Self-Organizing Neural Network Model for a
Mechanism of Pattern Recognition Unaffected by Shift in Position.
Biological Cybernetics, 36:193–202, 1980.
- [gabrielsson04movsom] Stefan Gabrielsson and Sam Gabrielsson.
MOVSOM-II - Analyzis and Visualization of Movieplot Clusters.
Uppsala University, Department of Information Technology, 2004.
- [goldberg92tapestry] David
Goldberg, David Nichols, Brian M. Oki, and Douglas Terry.
Using Collaborative Filtering to Weave an Information Tapestry.
Communications of the ACM, 35(12):61–70, 1992.
(doi:10.1145/138859.138867)
- [goldberg01eigentaste] Ken
Goldberg, Theresa Roeder, Dhruv Gupta, and Chris Perkins.
Eigentaste: A
Constant Time Collaborative Filtering Algorithm.
Information Retrieval, 4(2):133–151, 2001.
- [graef01application] Guntram
Graef and Christian Schaefer.
Application of ART2
Networks and Self-Organizing Maps to Collaborative Filtering.
In Revised Papers from the international Workshops OHS-7, SC-3, and AH-3
on Hypermedia: Openness, Structural Awareness, and Adaptivity, pages
296–309, 2001.
- [grossberg76adaptive] S. Grossberg.
Adaptive Pattern Classification and Universal Recoding, I: Parallel
Development and Coding of Neural Feature detectors.
Biological Cybernetics, 23:121–134, 1976.
- [haykin94neuralnetworks] S. Haykin.
Neural Networks : A Comprehensive Foundation.
Macmillan, New York, 1994.
- [herlocker99framework] Jonathan L. Herlocker, Joseph A. Konstan, Al Borchers, and
John Riedl.
An Algorithmic Framework for Performing Collaborative Filtering.
In SIGIR '99: Proceedings of the 22nd annual international ACM SIGIR
conference on Research and development in information retrieval, pages
230–237, New York, NY, USA, 1999. ACM Press.
(doi:10.1145/312624.312682)
- [herlocker00explaining] Jonathan L. Herlocker, Joseph A. Konstan, and John Riedl.
Explaining
Collaborative Filtering Recommendations.
In Computer Supported Cooperative Work, pages 241–250, 2000.
- [herlocker00understanding] Jonathan Lee Herlocker.
Understanding and Improving Automated Collaborative Filtering
Systems.
PhD thesis, University of Minnesota, 2000.
Adviser-Joseph A. Konstan.
- [hill95recommending] Will Hill,
Larry Stead, Mark Rosenstein, and George Furnas.
Recommending and Evaluating Choices in a Virtual Community of Use.
In CHI '95: Proceedings of the SIGCHI conference on Human factors in
computing systems, pages 194–201, New York, NY, USA, 1995. ACM
Press/Addison-Wesley Publishing Co.
(doi:10.1145/223904.223929)
- [honkela96newsgroup] Timo
Honkela, Samuel Kaski, Krista Lagus, and Teuvo Kohonen.
Newsgroup Exploration with WEBSOM Method and Browsing Interface.
Technical Report A32, Helsinki University of Technology, Laboratory of Computer
and Information Science, Espoo, Finland, 1996.
- [jacobi98patent] J.A. Jacobi
and E.A Benson.
System and Methods for Collaborative Recommendations.
US Patent No. 6,064,980, March 17 1998.
- [jain99data] A.K. Jain, M.N. Murty,
and P.J. Flynn.
Data Clustering: A
Review.
ACM Computing Surveys, 31(3):264–323, 1999.
- [jin99using] X Jin and
B Mobasher.
Using Semantic Similarity to Enhance Item-Based Collaborative
Filtering.
In Proceedings of The 2nd IASTED International Conference on Information
and Knowledge Sharing, Scottsdale, Arizona, 2003.
- [karlgren90algebra] Jussi Karlgren.
An Algebra for Recommendations: Using Reader Data as a Basis for
Measuring Document Proximity.
Technical Report 179, Swedish Institute of Computer Science (SICS), Stockholm
University, Stockholm, Sweden, 1990.
- [karlgren94newsgroup] Jussi Karlgren.
Newsgroup Clustering Based On User Behavior — A Recommendation
Algebra.
Technical Report T94:04, Swedish Institute of Computer Science (SICS),
Stockholm University, Stockholm, Sweden, 1994.
- [karypis01evaluation] George Karypis.
Evaluation of Item-Based Top-N Recommendation Algorithms.
In CIKM '01: Proceedings of the tenth international conference on
Information and knowledge management, pages 247–254, New York, NY,
USA, 2001. ACM Press.
(doi:10.1145/502585.502627)
- [kaski97thesis] Samuel Kaski.
Data Exploration Using Self-Organizing Maps.
PhD thesis, Helsinki University of Technology, Finland, March 1997.
Acta Polytechnica Scandinavica, Mathematics, Computing and Management in
Engineering Series No. 82.
- [kawamoto04cendant] Dawn Kawamoto.
Cendant Publishing has filed a lawsuit against Amazon.com, alleging patent
infringement.
CNet.com, 2004.
- [kohonen99where] T Kohonen and
R Hari.
Where the Abstract Feature Maps of the Brain Might Come From.
Trends in Neurosciences, 22(3):135–139, 1999.
- [kohonen00selforganization] Teuvo Kohonen, Samuel Kaski, Krista Lagus, Jarkko
Salojärvi, Jukka Honkela, Vesa Paatero, and Antti Saarela.
Self-Organization
of a Massive Document Collection.
IEEE Transactions on Neural Networks, 11:574–585, May 2000.
- [kohonen82selforganizing] T. Kohonen.
Self-Organizing Formation of Topologically Correct Feature Maps.
Biological Cybernetics, 43:59–69, 1982.
- [kohonen88neural] Teuvo Kohonen.
The "Neural" Phonetic Typewriter.
IEEE Computer, 21(3):11–22, 1988.
- [kohonen90som] T. Kohonen.
The Self-Organizing Map.
In Proceedings of the IEEE, volume 78, pages 1464–1480, 1990.
- [kohonen93things] T. Kohonen.
Things You Haven't Heard About the Self-Organizing Map.
In Proceedings of the IEEE International Conference on Neural
Networks, volume 3, pages 1147–1156, 1993.
- [kohonen01som] Teuvo Kohonen.
Self-Organizing Maps.
Springer, Berlin, third edition, 2001.
- [lagus00thesis] K. Lagus.
Text Mining with the WEBSOM.
PhD thesis, Helsinki University of Technology, Finland, 2000.
Acta Polytechnica Scandinavica, Mathematics and Computing Series no. 110.
- [lam04shilling] Shyong K. Lam and
John Riedl.
Shilling Recommender Systems for Fun and Profit.
In WWW '04: Proceedings of the 13th international conference on World
Wide Web, pages 393–402, New York, NY, USA, 2004. ACM Press.
(doi:10.1145/988672.988726)
- [lee02hybrid] Meehee Lee, Pyungseok
Choi, and Yongtae Woo.
A Hybrid Recommender System Combining Collaborative Filtering with
Neural Network.
In AH '02: Proceedings of the Second International Conference on
Adaptive Hypermedia and Adaptive Web-Based Systems, pages 531–534,
London, UK, 2002. Springer-Verlag.
- [linden03amazon] G. Linden,
B. Smith, and J. York.
Amazon.com Recommendations: Item-To-Item Collaborative Filtering.
Internet Computing, IEEE, 7(1):76–80, 2003.
- [luhn58automatic] H. P. Luhn.
The Automatic Creation of Literature Abstracts.
IBM Journal of Research Development, 2(2):159–165, 1958.
- [luhn58business] H. P. Luhn.
A Business Intelligence System.
IBM Journal of Research Development, 2(4):314–319, 1958.
- [lyman03howmuch] P. Lyman, H. R.
Varian, P. Charles, N. Good, L. L. Jordan, and K. Swearingen.
How Much Information? 2003.
Technical report, UC Berkeley's School of Information Management and Systems,
2003.
url http://www2.sims.berkeley.edu/research/projects/how-much-info-2003.
- [malone87communication] Thomas W.
Malone, Kenneth R. Grant, Franklyn A. Turbak, Stephen A. Brobst, and
Michael D. Cohen.
Intelligent
Information-Sharing Systems.
Communications of the ACM, 30(5):390–402, May 1987.
- [massa04trust] Paolo Massa
and Paolo Avesani.
Trust-Aware Collaborative Filtering for Recommender Systems.
In Proceedings of Federated International Conference On The Move to
Meaningful Internet: CoopIS, DOA, ODBASE, pages 492–508,
2004.
- [mclaughlin04collaborative] Matthew R. McLaughlin and Jonathan L. Herlocker.
A Collaborative Filtering Algorithm and Evaluation Metric that
Accurately Model the User Experience.
In SIGIR '04: Proceedings of the 27th annual international ACM
SIGIR conference on Research and development in information
retrieval, pages 329–336, New York, NY, USA, 2004. ACM Press.
(doi:10.1145/1008992.1009050)
- [mellville02conentboosted] Prem
Melville, Raymod J. Mooney, and Ramadass Nagarajan.
Content-boosted collaborative filtering for improved recommendations.
In Proceedings of the 18th National Conference on Artificial
Intelligence, pages 187–192, Menlo Park, CA, USA, 2002. American
Association for Artificial Intelligence.
- [montaner03taxonomy] M. Montaner, B. López, and J. L. De La Rosa.
A Taxonomy of Recommender Agents on the Internet.
Artificial Intelligence Review, 19(4):285–330, June 2003.
- [novak03discovering] Jasminko
Novak, Michael Wurst, Monika Fleischmann, and Wolfgang Strauss.
Discovering, Visualizing, and Sharing Knowledge through Personalized
Learning Knowledge Maps.
In Agent Mediated Knowledge Management, International Symposium
AMKM, pages 213–228, 2003.
- [oard97stateoftheart] Douglas W. Oard.
The State of the Art in Text Filtering.
User Modeling and User-Adapted Interaction, 7(3):141–178, 1997.
- [odonovan05trust] John
O'Donovan and Barry Smyth.
Trust in Recommender Systems.
In IUI '05: Proceedings of the 10th international conference on
Intelligent user interfaces, pages 167–174, New York, NY, USA, 2005.
ACM Press.
(doi:10.1145/1040830.1040870)
- [pampalk01islands] Elias Pampalk.
Islands of Music
- Analysis, Organization, and Visualization of Music Archives.
Master's thesis, Vienna University of Technology, Austria, December 2001.
- [pazzani96syskill] Michael J.
Pazzani, Jack Muramatsu, and Daniel Billsus.
Syskill & Webert: Identifying Interesting Web Sites.
In Proceedings of the Thirteenth National Conference on Artificial
Intelligence (AAAI-96), pages 54–61, August 1996.
- [pazzani99framework] Michael J.
Pazzani.
A Framework for
Collaborative, Content-Based and Demographic Filtering.
Artificial Intelligence Review, 13(5-6):393–408, 1999.
- [resnick97recommender] Paul
Resnick and Hal Varian.
Recommender Systems.
Communications of the ACM, 40(3):56–58, 1997.
- [resnick94grouplens] Paul
Resnick, Neophytos Iacovou, Mitesh Suchak, Peter Bergstrom, and John Riedl.
Grouplens: an Open Architecture for Collaborative Filtering of
Netnews.
In CSCW '94: Proceedings of the 1994 ACM conference on Computer
supported cooperative work, pages 175–186, New York, NY, USA, 1994.
ACM Press.
- [riedl05introduction] John
Riedl and Paul Dourish.
Introduction to the special section on recommender systems.
ACM Transactions on Computer-Human Interaction, 12(3):371–373,
September 2005.
- [roh03cbr] Tae Hyup Roh, Kyong Joo
Oh, and Ingoo Han.
A Cluster-Indexing CBR Model for Collaborative Filtering
Recommendation.
In Proceedings of the 7th Pacific Asia Conference on information
Systems, pages 150–167, July 2003.
- [salton88termweighting] Gerard Salton and Christopher Buckley.
Term-Weighting Approaches in Automatic Text Retrieval.
Information Processing and Management, 24(5):513–523, 1988.
- [salton83introduction] Gerard
Salton and Michael Mcgill.
Introduction to Modern Information Retrieval.
McGraw-Hill Education, August 1983.
- [salton71smart] G. Salton.
The SMART Retrieval System: Experiments in Automatic Document
Processing.
Prentice-Hall, Inc., Upper Saddle River, NJ, USA, 1971.
- [sammon69nonlinear] John W.
Sammon Jr.
A Nonlinear Mapping for Data Structure Analysis.
IEEE Transactions on Computers, C-18(5):401–409, 1969.
- [sant04dictonary] Paul M. Sant.
optimization problem.
in Dictionary of Algorithms and Data Structures [online], Paul E. Black,
ed., U.S. National Institute of Standards and Technology, 10 January 2005
2005.
(accessed 17 August 2006) Available from:
url http://www.nist.gov/dads/HTML/optimization.html.
- [sarwar98using] Badrul M. Sarwar,
Joseph A. Konstan, Al Borchers, Jonathan L. Herlocker, Bradley N. Miller, and
John Riedl.
Using Filtering Agents to
Improve Prediction Quality in the Grouplens Research
Collaborative Filtering System.
In Proceedings of the 1998 ACM Conference on Computer Supported
Cooperative Work, pages 345–354, 1998.
- [sarwar00application] B. Sarwar,
G. Karypis, J. Konstan, and J. Riedl.
Application of Dimensionality Reduction in Recommender Systems–A
Case Study.
In Proceedings of the WebKDD 2000 Workshop at the ACM-SIGKDD Conference
on Knowledge Discovery in Databases (KDD'00), 2000.
- [sarwar00analysis] Badrul
Sarwar, George Karypis, Joseph Konstan, and John Riedl.
Analysis of Recommendation Algorithms for E-Commerce.
In EC '00: Proceedings of the 2nd ACM conference on Electronic
commerce, pages 158–167, New York, NY, USA, 2000. ACM Press.
- [sarwar01itembased] Badrul M.
Sarwar, George Karypis, Joseph A. Konstan, and John Reidl.
Item-Based
Collaborative Filtering Recommendation Algorithms.
In Proceedings of the 10th international WWW Conference, pages
285–295, 2001.
- [schafer01ecommerce] J. Ben
Schafer, Joseph A. Konstan, and John Riedl.
E-Commerce
Recommendation Applications.
Data Mining and Knowledge Discovery, 5(1/2):115–153, 2001.
- [shani02mdp] Guy Shani, Ronen
Brafman, and David Heckerman.
An MDP-Based Recommender System.
In Proceedings of the 18th Annual Conference on Uncertainty in Artificial
Intelligence (UAI-02), pages 453–460, San Francisco, CA, 2002.
Morgan Kaufmann.
- [shardanand95social] Upendra Shardanand and Patti Maes.
Social Information
Filtering: Algorithms for Automating ``Word of Mouth''.
In Proceedings of ACM CHI'95 Conference on Human Factors in Computing
Systems, volume 1, pages 210–217, 1995.
- [silaghi04bidimensional] Gheorghe Cosmin Silaghi.
Bi-Dimensional Visualization of Target Categories for a Text
Categorization Task.
In IEEE Conference on Advances in Intelligent Systems: Theory and
Applications, AISTA 2004, November 2004.
- [singhal01modern] Amit Singhal.
Modern Information Retrieval: A Brief Overview.
IEEE Data Engineering Bulletin, 24(4):35–43, 2001.
- [sinha02role] Rashmi Sinha
and Kirsten Swearingen.
The Role of Transparency in Recommender Systems.
In CHI '02: CHI '02 extended abstracts on Human factors in computing
systems, pages 830–831, New York, NY, USA, 2002. ACM Press.
- [sirosh93how] Joseph
Sirosh and Risto Miikkulainen.
How Lateral Interaction
Develops in a Self-Organizing Feature Map.
In Proceedings of ICNN'93 International Conference on Neural
Networks, volume III, pages 1360–1365, Piscataway, NJ, 1993. IEEE
Service Center.
- [stack97patent] C. Stack.
System and Method for Providing Recommendation of Goods or Services
Based on Recorded Purchasing History.
US Patent No. 6,782,370, September 4 1997.
- [swearingen01beyond] Kirsten Swearingen and Rashmi Sinha.
Beyond Algorithms: An HCI Perspective on Recommender Systems.
ACM SIGIR 2001 Workshop on Recommender Systems, 2001.
- [swearingen02interaction] Kirsten Swearingen and Rashmi Sinha.
Interaction Design for Recommender Systems.
Designing Interactive Systems, 2002.
- [samand92selforganization] T.Samad and S.A.Harp.
Self-Organization with Partial Data.
Network: Computation in Neural Systems, 3:205–212, 1992.
- [vanrijsbergen79information] C. J. Van Rijsbergen.
Information Retrieval, 2nd edition.
Department of Computer Science, University of Glasgow, 2 edition, 1979.
- [vembu04selforganizing] Shankar Vembu and Stephan Baumann.
A Self-Organizing Map Based Knowledge Discovery for Music
Recommendation Systems.
In Proceedings of the 2nd International Symposium on Computer Music
Modeling and Retrieval, pages 119–129, 2004.
- [venna01neighborhood] Jarkko
Venna and Samuel Kaski.
Neighborhood Preservation in Nonlinear Projection Methods: An
Experimental Study.
In ICANN '01: Proceedings of the International Conference on Artificial
Neural Networks, pages 485–491, London, UK, 2001. Springer-Verlag.
- [vesanto00clustering] J. Vesanto and E. Alhoniemi.
Clustering of the
Self-Organizing Map.
IEEE Transactions on Neural Networks, 11(3):586–600, May
2000.
- [vesanto00som] J. Vesanto,
J. Himberg, E. Alhoniemi, and J. Parhankangas.
SOM Toolbox for Matlab.
Technical Report A57, Helsinki University of Technology, April 2000.
- [vesanto99sombased] J. Vesanto.
SOM-Based Data
Visualization Methods.
Intelligent Data Analysis, 3(2):111–126, 1999.
- [vondermalsburg73selforganization] Christoph von der Malsburg.
Self-Organization of
Orientation-Sensitive Cells in the Striate Cortex.
Kybernetik, 15:85–100, 1973.
- [widrow90perceptrons] Bernard
Widrow and Michael A. Lehr.
Perceptrons, Adalines, and Backpropagation.
In M.A. Arbib, editor, The handbook of brain theory and neural
networks, pages 871–877. MIT Press, Cambridge, MA, USA, 2 edition,
2003.
- [wilkes97bain] A.L. Wilkes and
N.J. Wade.
Bain on Neural Networks.
Brain and Cognition, 33(3):295–305, 1997.
- [willshaw76how] D. J. Willshaw and C. von der Malsburg.
How Patterned Neural Connections can be set up by Self-Organization.
Proceedings of the Royal Society of London Series B, 194:431–445,
1976.