Collaborative filtering using electrical resistance network models

Lecture Notes in Computer Science (including subseries Lecture Notes in Artificial Intelligence and Lecture Notes in Bioinformatics)

Volumn 4597 LNCS, Issue , 2007, Pages 269-282

  Kunegis, Jérôme ^a   Schmidt, Stephan ^a  

^a TECHNISCHE UNIVERSITÄT BERLIN   (Germany)

Author keywords

[No Author keywords available]

Indexed keywords

DATA STRUCTURES; ELECTRIC RESISTANCE; INFORMATION SYSTEMS; LEARNING ALGORITHMS; USER INTERFACES;

RESISTANCE DISTANCE; WEIGHTED EDGES;

COMPUTER SUPPORTED COOPERATIVE WORK;

EID: 37249024765     PISSN: 03029743     EISSN: 16113349     Source Type: Book Series    
DOI: 10.1007/978-3-540-73435-2_21     Document Type: Conference Paper

References (10)

1. Fouss, F., Pirotte, A., Saerens, M.: The application of new concepts of dissimilarities between nodes of a graph to collaborative filtering. ACM Trans. Math. Softw. (2003), Also TR-03-010 at www.cise.ufl.edu/tech-reports
2. Billsus, D., Pazzani, M.J.: Learning collaborative information filters. In: Proc. 15th International Conf. on Machine Learning, pp. 46-54. Morgan Kaufmann, San Francisco (1998)
3. Breese, J.S., Heckerman, D., Kadie, C.: Empirical analysis of predictive algorithms for collaborative filtering. In: Proc. of the Fourteenth Annual Conference on Uncertainty in Artificial Intelligence, pp. 43-52 (1998)
4. Mirza, B.J., Keller, B.J., Ramakrishnan, N.: Evaluating recommendation algorithms by graph analysis. CoRR cs.IR/0104009 (2001)
5. Keller, B.J., mi Kim, S., Vemuri, N.S., Ramakrishnan, N., Perugini, S.: The good, bad and the indifferent: Explorations in recommender system health, San Diego, California (2005), http://www.grouplens.org/beyond2005/full/keller. pdf
6. Klein, D.J.: Resistance-distance sum rules. Croatica Chemica Acta 75(2), 633-649 (2002)
7. Qin, Z., Cheng, C.K.: Linear network reduction via Y-Δ- Transformation. technical report 2002-0706, University of California, San Diego, United States (2002)
8. George, A., Liu, W.H.: The evolution of the minimum degree ordering algorithm. SIAM Rev. 31(1), 1-19 (1989)
9. Heggemes, P., Eisenstat, S., Kumfert, G., Pothen, A.: The computational complexity of the minimum degree algorithm (2001)
10. Herlocker, J.L., Konstan, J.A., Terveen, L.G., Riedl, J.T.: Evaluating collaborative filtering recommender systems. ACM Trans. Inf. Syst. 22(1), 5-53 (2004)