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%
% References used in papers by Jérôme Kunegis. These are references I
% use a lot, so they are put here, where they can be cited from any
% publication.
%
% References have names of the form b<N>, where <N> is a number.
%
% This file is incomplete. It only contains references I have actually
% cited somewhere. References I've never cited may only be listed in
% the file 'OLD', explaining the gaps in the numbers here.
%
@inproceedings{b4,
title = {Extracting Large-Scale Knowledge Bases from the {Web}},
author = {Ravi Kumar and Prabhakar Raghavan and Srdhar
Rajagolapan and Andrew Tomkins},
notes = {Finding complete unidirectional bipartite subgraphs of
the directed link graph of the web. (Apply to the
user/document bipartite graph)},
booktitle = {Proc. Int. Conf. on Very Large Data Bases},
year = {1999},
pages = {639--650},
}
@inproceedings{b6,
title = {Smoothing of Recommenders' Ratings for Collaborative
Filtering},
author = {Han-Shen Huang and Chun-Nan Hsu},
booktitle = {Proc. Conf. on Artif. Intell. and Appl.},
year = {2001},
}
@article{b7,
author = {Ken Goldberg and Theresa Roeder and Dhruv Gupta and
Chris Perkins},
title = {{Eigentaste}: A Constant Time Collaborative Filtering
Algorithm},
journal = {Inf. Retrieval},
volume = {4},
number = {2},
year = {2001},
pages = {133--151},
}
@misc{b8,
author = {Panagiotis Symeonidis Alexandros},
title = {Nearest-biclusters Collaborative Filtering},
}
@inproceedings{b10,
title = {An Algorithmic Framework for Performing Collaborative
Filtering},
author = {Jonathan Herlocker and Joseph Konstan and Al Borchers
and John Riedl},
booktitle = {Proc. Int. Conf. on Res. and Dev. in
Inf. Retrieval},
year = {1999},
pages = {230--237},
}
@article{b11,
title = {Evaluating Collaborative Filtering Recommender
Systems},
author = {Jonathan Herlocker and Joseph Konstan and Loren
Terveen and John Riedl},
journal = {ACM Trans. Inf. Syst.},
volume = {22},
number = {1},
year = {2004},
pages = {5--53},
}
@inproceedings{b12,
author = {Charu C. Aggarwal and Joel L. Wolf and Kun-Lung Wu and
Philip S. Yu},
title = {Horting Hatches an Egg: A New Graph-theoretic Approach
to Collaborative Filtering},
booktitle = {Proc. Int. Conf. on Knowl. Discov. and Data Min.},
year = {1999},
pages = {201--212},
}
@article{b13,
title = {Studying Recommendation Algorithms by Graph Analysis},
author = {Batul J. Mirza and Benjamin J. Keller and Naren
Ramakrishnan},
year = {2001},
journal = {Intell. Inf. Syst.},
volume = {20},
number = {2},
pages = {131--160},
}
@inproceedings{b15,
title = {The Application of New Concepts of Dissimilarities
between Nodes of a Graph to Collaborative Filtering},
author = {François Fouss and Alain Pirotte and Marco Saerens},
year = {2004},
booktitle = {Proc. Workshop on Stat. Approaches for Web Min.},
pages={26--37},
}
@article{b16,
author = {Douglas J. Klein},
title = {Resistance-Distance Sum Rules},
journal = {Croatica Chemica Acta},
volume = {75},
number = {2},
year = {2002},
pages = {633--649},
}
@article{b18,
title = {Theory of Resistor Networks: the Two-point Resistance},
author = {F.~Y. Wu},
journal = {J. Phys. A},
volume = {37},
pages = {6653--6673},
year = {2004}
}
@book{b19,
title = {Random Walks and Electric Networks},
author = {Doyle, Peter G. and Snell, J. Laurie},
year = {1984},
publisher = {Math. Ass. of Am.},
notes = { Includes algorithms to calculate equivalent
resistance: Monte-Carlo, Relaxation, Markov chains },
}
@inproceedings{b25,
title = {Empirical Analysis of Predictive Algorithms for
Collaborative Filtering},
author = {Breese, John S. and Heckerman, David and Kadie, Carl},
booktitle= {Proc. Conf. on Uncertain. in Artif. Intell.},
year = {1998},
pages = {43--52},
notes = {
early comparative study of collaborative filtering
methods
}
}
@inproceedings{b26,
title = {Social Information Filtering: Algorithms for Automating
`Word of Mouth'},
author = {Upendra Shardanand and Patti Maes},
booktitle = {Proc. Conf. on Human Factors in Comput. Syst.},
volume = {1},
pages = {210--217},
year = {1995},
}
@article{b27,
author = {Jon Kleinberg},
title = {Authoritative Sources in a Hyperlinked Environment},
journal = {J. ACM},
volume = {46},
number = {5},
year = {1999},
pages = {604--632},
notes = {
The main HITS reference.
Finding hubs and authorities in a directed graph from a
hyperlinked document structure. Presented as
post-retrieval step.
}
}
@inproceedings{b29,
title = {A Joint Framework for Collaborative and Content
Filtering},
author = {Justin Basilico and Thomas Hofmann},
booktitle = {Proc. Int. Conf. on Res. and Dev. in
Inf. Retrieval},
year = {2004},
pages = {550--551}
}
@inproceedings{b30,
title = {Unifying Collaborative and Content-based Filtering},
author = {Justin Basilico and Thomas Hofmann},
booktitle = {Proc. Int. Conf. on Mach. Learn.},
year = {2004},
}
@inproceedings{b31,
title = {Collaborative Filtering via {Gaussian} Probabilistic
Latent Semantic Analysis},
author = {Thomas Hofmann},
booktitle = {Proc. Int. Conf. on Res. and Dev. in
Inf. Retrieval},
year = {2003},
pages = {259--266},
}
@article{b33,
title = {Item-based Top-{N} Recommendation Algorithms},
author = {Mukund Deshpande and George Karypis},
journal = {ACM Trans. Inf. Syst.},
volume = {22},
number = {1},
year = {2004},
pages = {143--177},
notes = {About recommendation datasets (ie. values are only 0
and 1)},
}
@article{b34,
title = {Latent Semantic Models for Collaborative Filtering},
author = {Thomas Hofmann},
journal = {ACM Trans. Inf. Syst.},
volume = {22},
number = {1},
year = {2004},
pages = {89--115},
}
@inproceedings{b36,
title = {Information Retrieval based on Collaborative Filtering
with Latent Interest Semantic Map},
author = {Noriaki Kawamae and Katsumi Takahashi},
booktitle = {Proc. Int. Conf. on Knowl. Discov. and Data Min.},
year = {2005},
pages = {618--623},
}
@inproceedings{b37,
title = {Recommendation Algorithm Combining the User-based
Classified Regression and the Item-based Filtering},
author = {Yu Chuan and Xu Jieping and Du Xiaoyong},
booktitle = {Proc. Int. Conf. on Electronic Commerce},
year = {2006},
pages = {574--578},
}
@inproceedings{b41,
title = {Document Retrieval and Clustering: From Principal
Component Analysis to Self-aggregation Networks},
author = {Chris H. Q. Ding},
booktitle = {Proc. Int. Workshop on Artif. Intell. and Stat.},
year = {2003},
}
@inproceedings{b42,
title = {Explaining Collaborative Filtering Recommendations},
author = {Jonathan Herlocker and Joseph Konstan and John Riedl},
booktitle = {Comput. Supported Cooperative Work},
pages = {241--250},
year = {2000},
}
@inproceedings{b43,
author = {M. Connor and Jonathan Herlocker},
title = {Clustering Items for Collaborative Filtering},
year = {2001},
booktitle = {Proc. SIGIR Workshop on Recomm. Syst.},
}
@inproceedings{b44,
author = {Matthew R. McLaughlin and Jonathan Herlocker},
title = {A Collaborative Filtering Algorithm and Evaluation
Metric That Accurately Model the User Experience},
booktitle = {Proc. Int. Conf. on Res. and Dev. in
Inf. Retrieval},
year = {2004},
pages = {329--336},
}
@article{b54,
title = {Probabilistic Memory-Based Collaborative Filtering},
author = {Kai Yu and Anton Schwaighofer and Volker Tresp and
Xiaowei Xu and Hans-Peter Kriegel},
journal = {Trans. on Knowl. and Data Engineering},
volume = {16},
number = {1},
year = {2004},
pages = {56--69},
}
@inproceedings{b55,
author = {Rong Jin and Luo Si and ChengXiang Zhai and Jamie
Callan},
title = {Collaborative Filtering with Decoupled Models for
Preferences and Ratings},
booktitle = {Proc. Int. Conf. on Inf. and Knowl. Manag.},
year = {2003},
pages = {309--316},
}
@inproceedings{b56,
author = {Michael P. O'Mahony and Neil J. Hurley and Guenole
C. M. Silvestre},
title = {Utility-based neighbourhood formation for efficient and
robust collaborative filtering},
booktitle = {Proc. Conf. on Electronic Commerce},
year = {2004},
pages = {260--261},
}
@article{b59,
title = {Statistical Mechanics of Complex Networks},
author = {Réka Albert and Albert-Laszló Barabási},
journal = {Rev. of Mod. Phys.},
number = {1},
pages = {47--97},
volume = {74},
year = {2002},
notes = {
#: Random graph models.
#: Examples of the power law exponent γ
},
}
@inproceedings{b67,
author = {Ravi Kumar and Uma Mahadevan and D. Sivakumar},
title = {A Graph-theoretic Approach to Extract Storylines from
Search Results},
booktitle = {Proc. Int. Conf. on Knowl. Discov. and Data Min.},
year = {2004},
pages = {216--225},
}
@inproceedings{b68,
title = {A Graph-based Recommender System for Digital Library},
author = {Huang, Zan and Chung, Wingyan and Ong, Thian-Huat and
Chen, Hsinchun },
booktitle = {Proc. Int. Conf. on Digital Libraries},
pages = {65--73},
priority = {3},
year = {2002}
}
@inproceedings{b70,
author = {Bin Gao and Tie-Yan Liu and Xin Zheng and Qian-Sheng
Cheng and Wei-Ying Ma},
title = {Consistent Bipartite Graph Co-partitioning for
Star-structured High-order Heterogeneous Data
Co-clustering},
booktitle = {Proc. Int. Conf. on Knowl. Discov. and Data Min.},
year = {2005},
pages = {41--50},
}
@inproceedings{b73,
author = {L. Ungar and D. Foster},
title = {A formal statistical approach to collaborative
filtering},
year = {1998},
booktitle= {Proc. Conf. on Automated Learn. and Discov.},
}
@inproceedings{b75,
author = {D. Nichols},
title = {Implicit Rating and Filtering},
pages = {31--36},
booktitle = {Proc. DELOS Workshop on Filtering and Collaborative
Filtering},
year = {1998}
}
@inproceedings{b77,
author = {David Pennock and Eric Horvitz and Steve Lawrence and
C. Lee Giles},
title = {Collaborative Filtering by Personality Diagnosis: A Hybrid
Memory- and Model-based Approach},
booktitle = {Proc. Conf. on Uncertain. in Artif. Intell.},
pages = {473--480},
year = {2000},
}
@inproceedings{b78,
author = {Gui-Rong Xue and Chenxi Lin and Qiang Yang and WenSi
Xi and Hua-Jun Zeng and Yong Yu and Zheng Chen},
title = {Scalable Collaborative Filtering using Cluster-based
Smoothing},
booktitle = {Proc. Int. Conf. on Res. and Dev. in
Inf. Retrieval},
year = {2005},
pages = {114--121},
}
@article{b79,
title = {Solving Cluster Ensemble Problems by Bipartite Graph
Partitioning},
author = {Xiaoli Zhang Fern and Carla E. Brodley},
}
@article{b80,
title = {Bipartite Graphs as Models of Complex Networks},
author = {Jean-Loup Guillaume and Matthieu Latapy},
notes = {
#: A random graph model for unipartite graphs, which
modesl them as the projection of a random bipartite
graphs, in which both types of nodes have their own
degree distribution. The projection ensures that the
resulting graph has high clustering coefficient
values. No closed-form expressions are given.
},
}
@inproceedings{b82,
author = {Paul Resnick and N. Iacovou and M. Suchak and
P. Bergstorm and John Riedl},
title = {{GroupLens}: An Open Architecture for Collaborative
Filtering of {NetNews}},
booktitle = {Proc. Conf. on Comput. Supported Cooperative Work},
pages = {175--186},
year = {1994},
}
@article{b83,
author = {David Goldberg and David Nichols and Brian M. Oki and
Douglas Terry},
title = {Using collaborative filtering to weave an information
tapestry},
journal = {Commun. ACM},
volume = {35},
number = {12},
year = {1992},
pages = {61--70},
}
@book{b89,
title = {{Markov} Random Fields: Theory and Application},
author = {Rama Chellappa and Anil Jain},
year = {1993},
publisher = {Academic Press},
}
@book{b95,
title = {Probabilistic Reasoning in Intelligent Systems:
Networks of Plausible Inference},
author = {Judea Pearl},
year = {1988},
isbn = {0-934613-73-7},
publisher = {Morgan Kaufmann Publishers Inc.},
}
@book{b96,
author = {Yurii A. Rozanov},
title = {Markov Random Fields},
year = {1983},
publisher = {Springer},
}
@article{b97,
author = {Xiao, Wenjun and Gutman, Ivan },
journal = {Theoretica Chimica Acta},
number = {4},
pages = {284--289},
title = {Resistance Distance and {Laplacian} Spectrum},
volume = {110},
year = {2003}
}
@article{b101,
author = {Douglas J. Klein and Milan Randić},
title = {Resistance Distance},
journal = {J. Math. Chem.},
volume = {12},
number = {1},
year = {1993},
pages = {81--95},
}
@article{b105,
title = {Random-walk Computation of Similarities between Nodes of
a Graph with Application to Collaborative
Recommendation},
author = {François Fouss and Alain Pirotte and Jean-Michel Renders
and Marco Saerens},
journal = {Trans. on Knowl. and Data Engineering},
volume = {19},
number = {3},
year = {2007},
pages = {355--369},
}
@inproceedings{b107,
title = {A Novel Way of Computing Similarities between Nodes of
a Graph, with Application to Collaborative
Recommendation},
author = {François Fouss and Alain Pirotte and Marco Saerens},
booktitle = {Proc. Int. Conf. on Web Intell.},
year = {2005},
pages = {550--556},
}
@inproceedings{b112,
title = {Distance-Free Image Retrieval Based on Stochastic
Diffusion over Bipartite Graphs},
author = {Christian Bauckhage},
booktitle = {Br. Mach. Vision Conf.},
year = {2007},
pages = {1--10},
}
@inproceedings{b113,
title = {Why Does Collaborative Filtering Work? --
Recommendation Model Validation and Selection by
Analyzing Bipartite Random Graphs},
author = {Zan Huang and Daniel D. Zeng},
booktitle = {Proc. Workshop of Inf. Technol. and Syst.},
year = {2005},
}
@article{b114,
author = {Zan Huang and Hsinchun Chen and Daniel Zeng},
title = {Applying Associative Retrieval Techniques to Alleviate
the Sparsity Problem in Collaborative Filtering},
journal = {ACM Trans. Inf. Syst.},
volume = {22},
number = {1},
year = {2004},
pages = {116--142},
}
@book{b116,
title = {Modern Graph Theory},
author = {Béla Bollobás},
year = {1998},
publisher = {Springer},
_notes = {
Has several chapters about resistance graphs,
resistance distance and the Laplacian matrix.
},
}
@book{b117,
title = {Eigenspaces of Graphs},
author = {Dragoš Cvetković and Peter Rowlinson and Slobodan
Simić},
year = {1997},
publisher = {Cambridge Univ. Press},
}
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