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Ph.D. Disszertáció/Thesis



A. A. Benczúr.

Cut structures and randomized algorithms in edge-connectivity problems.

PhD thesis, Department of Mathematics, Massachusetts Institute of Technology, June 1997.

is cited by (11)

A new approach to cactus construction applied to TSP support graphs. K Wenger - Integer Programming and Combinatorial Optimization, 2006

and by

Ashish Goel, Michael Kapralov, and Sanjeev Khanna. 2010. Perfect matchings via uniform sampling in regular bipartite graphs. ACM Trans. Algorithms 6, 2, Article 27 (April 2010), 13 pages.

and by

Goel, A. and Kapralov, M. and Khanna, S., Perfect matchings via uniform sampling in regular bipartite graphs, Proceedings of the Nineteenth Annual ACM-SIAM Symposium on Discrete Algorithms, pp 11-17, 2009

and by

Fast edge splitting and Edmonds' arborescence construction for unweighted graphs

A Bhalgat, R Hariharan, T Kavitha, D Panigrahi - Proceedings of the nineteenth annual ACM-SIAM symposium on Theory of Computing, 2008

and by

Perfect Matchings via Uniform Sampling in Regular Bipartite Graphs
A Goel, M Kapralov, S Khanna - Arxiv preprint arXiv:0811.2457, 2008

and by

A Fast Edge-Splitting Algorithm in Edge-Weighted Graphs

Hiroshi NAGAMOCHI

IEICE Transactions on Fundamentals of Electronics, Communications and

Computer Sciences 2006 E89-A(5):1263-1268


and by

I. A. Nazarova

Models and methods for solving the problem of network vulnerability

Journal of Computer and Systems Sciences International

Volume 45, Number 4 / July, 2006

Pages 567-578


and by

Michel X. Goemans, Approximate Edge Splitting


\textsl{SIAM Journal on Discrete Mathematics}

Volume 14, Number 1

pp. 138-141 (2001)

and by

L. Fleischer, Building the chain and cactus representations of all

minimum cuts from Hao--Orlin in same asymptotic run time. In R. Bixby,

E. A. Boyd, and R. Z. Rios Mercado, editors, Integer Programming and

Combinatorial Optimization, Lecture Notes in Computer

Science. Springer-Verlag, June 1998. Extended Abstract.

and by

Fleischer L, Building chain and cactus representations of all minimum cuts from Hao-Orlin in the same asymptotic run time J ALGORITHM 33: (1) 51-72 OCT 1999

and by

L. Fleischer. Separating Maximally Violated Comb Inequalities in

Planar Graphs. PhD thesis, Cornell University, Ithaca, NY, August 1997


Konferenciacikkek/Conference Proceedings

Ádám Gyenge, Janne Sinkkonen, and András A. Benczúr. 2010. An efficient block model for clustering sparse graphs. In Proceedings of the Eighth Workshop on Mining and Learning with Graphs (MLG '10). ACM, New York, NY, USA, 62-69.

Bálint Daróczy, István Petrás, András A. Benczúr, Dávid Nemeskey. SZTAKI @ ImageCLEF 2010. Conference on Multilingual and Multimodal Information Access Evaluation, 20-23 September 2010, Padua.

Bálint Daróczy, István Petrás, András A. Benczúr, Zsolt Fekete, Dávid Nemeskey, Dávid Siklósi, Zsuzsa Weiner. SZTAKI @ ImageCLEF 2009. ADVANCES IN MULTILINGUAL AND MULTIMODAL INFORMATION RETRIEVAL. 10th Workshop of the Cross-Language Evaluation Forum, CLEF 2009, Revised Selected Papers. Springer LNCS, 2010.

Bálint Daróczy, Daniele Falavigna, Roberto Gretter, Dávid Nemeskey, István Petrás, Róbert Pethes, András A. Benczúr. SZTAKI @ TRECVID 2010. In TRECVID 2010 Working Notes.

András Garzó, Dávid Nemeskey, Róbert Pethes, Dávid Siklósi, András A. Benczúr, SZTAKI @ TREC 2010, in TREC 2010 Working Notes.


Bálint Daróczy, István Petrás, András A. Benczúr, Zsolt Fekete, Dávid Nemeskey, Dávid Siklósi, Zsuzsa Weiner. SZTAKI @ ImageCLEF 2009. 10th Workshop of the Cross-Language Evaluation Forum, CLEF 2009.

Bálint Daróczy, Dávid Nemeskey, István Petrás, András A. Benczúr, Tamás Kiss. SZTAKI @ TRECVID 2009. In TRECVID 2009 Working Notes.

Miklós Erdélyi, András A. Benczúr, Julien Masanes and Dávid Siklósi. Web Spam Filtering in Internet Archives. In Proceedings of the 5th International Workshop on Adversarial Information Retrieval on the Web (AIRWeb), 2009.

István Bíró, Dávid Siklósi, Jácint Szabó and András Benczúr. Linked Latent Dirichlet Allocation in Web Spam Filtering. In Proceedings of the 5th International Workshop on Adversarial Information Retrieval on the Web (AIRWeb), 2009.

Is cited by (2)

Krestel, R. and Fankhauser, P. and Nejdl, W., Latent dirichlet allocation for tag recommendation, Proceedings of the third ACM conference on Recommender systems, pp 61-68, 2009

and by

Krestel, R. and Fankhauser, P.Tag Recommendation using Probabilistic Topic Models, ECML PKDD Discovery Challenge 2009 (DC09)


András A. Benczúr, Miklós Erdélyi, Julien Masanes and Dávid Siklósi. Web Spam Challenge Proposal for Filtering in Archives In Proceedings of the 5th International Workshop on Adversarial Information Retrieval on the Web (AIRWeb), 2009.

Increasing cluster recall of cross-modal image retrieval. S. Rácz, B. Daróczy, A. Pereszlényi, D. Siklósi, A. Benczúr, M. Brendel. In Working Notes of the 2008 CLEF Workshop, Aarhus, Denmark, Sept. 2008.

SZTAKI @ ImageCLEF 2008 Visual Concept Detection. B. Daróczy, Zs. Fekete, M. Brendel. in Working Notes of the 2008 CLEF Workshop, Aarhus, Denmark, Sept. 2008.

A. A. Benczúr, D. Siklósi, I. Bíró, Zs. Fekete, M. Kurucz, A. Pereszlényi, S. Rácz, A. Szabó, and J. Szabó. Web Spam: a Survey with Vision for the Archivist. In Proc. IWAW 2008.


Istvan Biro, Andras Benczur, Jacint Szabo and Ana Gabriela Maguitman. A Comparative Analysis of Latent Variable Models for Web Page Classification. In Proc LA-Web 2008.

I. Bíró, J. Szabó and A. A.Benczúr. Latent Dirichlet Allocation in Web Spam Filtering. In Proceedings of the 4th International Workshop on Adversarial Information Retrieval on the Web (AIRWeb), 2008.

Is cited by (3)

M Soranamageswari, Dr C Meena. Histogram based Image Spam Detection using Back propagation Neural Networks. Global Journal of Computer Science and Technology, Vol 9, No 5 (2010).

and by

Daud, A. and Li, J. and Zhou, L. and Muhammad, F. Knowledge discovery through directed probabilistic topic models: a survey, Frontiers of Computer Science in China 4(2), pp. 280-301, 2010

and by

Dai, N. and Davison, B.D. and Qi, X., Looking into the past to better classify web spam, Proceedings of the 5th International Workshop on Adversarial Information Retrieval on the Web, pp 1-8, 2009, ACM New York, NY, USA


A. A.Benczúr, I. Bíró, Zs. Fekete, M. Kurucz, A. Pereszlényi, S. Rácz, A. Szabó, and J. Szabó. Web Spam Hunting @ Budapest. In Proceedings of the 4th International Workshop on Adversarial Information Retrieval on the Web (AIRWeb), 2008.

Miklós Kurucz, András A. Benczúr, Attila Pereszlényi. Large-Scale Principal Component Analysis on LiveJournal Friends Network. In proc Workshop on Social Network Mining and Analysis Held in conjunction with The 13th ACM SIGKDD International Conference on Knowledge Discovery and Data Mining (KDD 2008) August 24-27, 2008, Las Vegas, NV

Is cited by (3)

Platos, J. and Kromer, P. and Snasel, V. and Abraham, A. Scaling IDS construction based on Non-negative Matrix factorization using GPU computing. Information Assurance and Security (IAS), 2010 Sixth International Conference, pp. 86—91, 2010.


and by

Platos, J. and Gajdos, P. and Krömer, P. and Snasel, V. Non-negative Matrix Factorization on GPU, Networked Digital Technologies, pp 21-30, 2010

and by

Platos, J. and Gajdos, P. Large data real-time classification with Non-negative Matrix Factorization and Self-Organizing Maps on GPU, International Conference on Computer Information Systems and Industrial Management Applications (CISIM), pp. 176-181. 2010.

A. A. Benczúr, I. Bíró, M. Brendel, K. Csalogány, B. Daróczy, and D. Siklósi. Cross-modal retrieval by text and image feature biclustering. In Working Notes of the 2007 CLEF Workshop, Budapest, Hungary, Sept. 2007.

P. Schönhofen, A. A. Benczúr, I. Bíró, and K. Csalogány. Performing cross-language retrieval with wikipedia. In Working Notes of the 2007 CLEFWorkshop, Budapest, Hungary, Sept. 2007.

András A. Benczúr, Károly Csalogány, László Lukács, Dávid Siklósi: Semi-Supervised Learning: A Comparative Study for Web Spam and Telephone User Churn. in Proc. Graph Labelling Workshop and Web Spam Challenge 2007 in conjunction with ECML/PKDD 2007.

Miklós Kurucz, András A. Benczúr, Tamás Kiss, István Nagy, Adrienn Szabó and Balázs Torma: Who Rated What: a combination of SVD, correlation and frequent sequence mining. in Proc. KDD Cup and Workshop 2007 in conjunction with KDD 2007.


Is cited by (7)

Harald Steck. 2010. Training and testing of recommender systems on data missing not at random. In Proceedings of the 16th ACM SIGKDD international conference on Knowledge discovery and data mining (KDD '10). ACM, New York, NY, USA, 713-722.


and by

Yeh, J. and Wu, M. Recommendation Based on Latent Topics and Social Network Analysis, Computer Engineering and Applications (ICCEA), 2010 Second International Conference, pp. 209—213, 2010

and by

Tsuyoshi Kato, Hisashi Kashima, Masashi Sugiyama, Kiyoshi Asai, "Conic Programming for Multi-Task Learning," IEEE Transactions on Knowledge and Data Engineering, 03 Jun. 2009.

and by


Pan, R. and Scholz, M., Mind the gaps: weighting the unknown in large-scale one-class collaborative filtering, Proceedings of the 15th ACM SIGKDD international conference on Knowledge discovery and data mining, pp. 667-676, 2009

and by

One-class collaborative filtering. R Pan, Y Zhou, B Cao, NN Liu, R Lukose, M. Proceedings of the 2008 Eighth IEEE International Conference on Data Mining, pp. 502—511, 2008.

and by

Mind the gaps: weighting the unknown in large-scale one-class collaborative filtering. R Pan, M Scholz. Proceedings of the 15th ACM SIGKDD international conference on Knowledge discovery and data mining, pp. 667—676, 2009.

and by

Collaborative Filtering on the example of the Net ix Prize.

P Ott. Diploma thesis, Anhalt University of applied sciences (FH) in Saxony-Anhalt, Germany


Miklós Kurucz, András A. Benczúr, Károly Csalogány: Methods for large scale SVD with missing values. in Proc. KDD Cup and Workshop 2007 in conjunction with KDD 2007.

is cited by (15)

Mohammad Khoshneshin and W. Nick Street. 2010. Collaborative filtering via euclidean embedding. In Proceedings of the fourth ACM conference on Recommender systems (RecSys '10). ACM, New York, NY, USA, 87-94.


and by

Use of multiple singular value decompositions to analyze complex intracellular calcium ion signals, Josue G. Martinez, Jianhua Z. Huang, Robert C. Burghardt, Rola Barhoumi, and Raymond J. Carroll, Ann. Appl. Stat. Volume 3, Number 4 (2009), 1467-1492.

and by

Pattern recognition and machine learning for magnetic resonance images with kernel methods, Chu, C.-Y.C. (2009) Pattern recognition and machine learning for magnetic resonance images with kernel methods. Doctoral thesis, UCL (University College London).

and by

Large-scale collaborative prediction using a nonparametric random effects model

K Yu, J Lafferty, S Zhu, Y Gong. Proceedings of the 26th Annual International Conference on Machine Learning, 2009.

and by

Fast nonparametric matrix factorization for large-scale collaborative filtering

K Yu, S Zhu, J Lafferty, Y Gong - The 32nd SIGIR conference, 2009.

and by

A Unified Approach to Building Hybrid Recommmender Systems.

A Gunawardana, C Meek, C Meek. ACM International Conference on Recommender Systems, 2009.

and by

Collaborative Filtering on the example of the Net ix Prize

P Ott. Diploma thesis, Anhalt University of applied sciences (FH) in Saxony-Anhalt, Germany

and by

Tensor Completion for Estimating Missing Values in Visual Data

J Liu, P Musialski, P Wonka, J Ye, ICCV 2009.


and by

Scalable Collaborative Filtering Approaches for Large Recommender Systems
G Takacs, I Pilaszy, B Nemeth, D Tikk - Journal of Machine Learning Research, 2009.

and by

Modeling Stroke Diagnosis with the Use of Intelligent Techniques

S Lalas, N Ampazis, A Tsakonas, G Dounias. Proceedings of the 5th Hellenic conference on Artificial Intelligence: Theories, Models and Applications, pp. 352—358, 2008.

and by

Incremental Matrix Factorization for Collaborative Filtering. P Ott. Contributions to Science, Technology and Design 01/2008, Anhalt University of applied sciences (FH), 2008

and by

Additive Regression Applied to a Large-Scale Collaborative Filtering Problem. E Frank, M Hall - Proceedings of the 21st Australasian Joint Conference on Artificial Intelligence: Advances in Artificial Intellige, 2008

Online-updating regularized kernel matrix factorization models for large-scale recommender systems
S Rendle, L Schmidt-Thieme - Proceedings of the 2008 ACM conference on Recommender systems, 2008

and by

Large-Scale Parallel Collaborative Filtering for the Netflix Prize
Y Zhou, D Wilkinson, R Schreiber, R Pan - Algorithmic Aspects in Information and Management, 2008

Miklós Kurucz, András A. Benczúr, Károly Csalogány, László Lukács: Spectral Clustering in Telephone Call Graphs. in Proc. WebKDD/SNAKDD Workshop 2007 in conjunction with KDD 2007.



is cited by (6)

Yu Wang, Gao Cong, Guojie Song, and Kunqing Xie. 2010. Community-based greedy algorithm for mining top-K influential nodes in mobile social networks. In Proceedings of the 16th ACM SIGKDD international conference on Knowledge discovery and data mining (KDD '10). ACM, New York, NY, USA, 1039-1048.

and by

Kung, H.T.;   Vlah, D.: Sign-based spectral clustering. Communications (QBSC), 2010 25th Biennial Symposium, pp 32 – 39, 2010.

and by

Narayanan, A. and Shmatikov, V., De-anonymizing Social Networks, Proceedings of the 2009 30th IEEE Symposium on Security and Privacy, pp 173-187, 2009

and by


Duan, D. and Li, Y. and Jin, Y. and Lu, Z., Community mining on dynamic weighted directed graphs, Proceeding of the 1st ACM international workshop on Complex networks meet information & knowledge management, pp 11-18, 2009

and by


Zhang, H. and Yen, J. and Giles, C.L. and Mombaster, B. and Spiliopoulou, M. and Srivastava, J. and Nasraoui, O. and McCallum, A., WebKDD/SNAKDD 2007: web mining and social network analysis post-workshop report, ACM SIGKDD Explorations Newsletter 9(2), pp 87-92, 2007

and by

Discovery of Social Groups Using Call Detail Records. H Zhang, R Dantu. Proceedings of the OTM Confederated International Workshops and Posters on On the Move to Meaningful Internet Systems: 2008, pp. 489—498.

and by

De-anonymizing social networks. A Narayanan, V Shmatikov - Imprint, 2009 - arxiv.org

András A. Benczúr, István Bíró, Károly Csalogány, Tamás Sarlós: Web Spam Detection via Commercial Intent Analysis. in Proc. Airweb 2007 in conjunction with WWW 2007.



is cited by

Benferhat, S. and Tabia, K. Binary naive possibilistic classifiers: Handling uncertain inputs. International Journal of Intelligent Systems 24(12), 2009, Wiley Online Library

and by

Pera, M.S. and Ng, Y.K., A structural, content-similarity measure for detecting spam documents on the web, International Journal of Web Information Systems 5(4), pp 431-464, 2009, Emerald Group Publishing Limited

and by

Zhou, B. and Pei, J., Link spam target detection using page farms. ACM Transactions on Knowledge Discovery from Data (TKDD) 3(3) 2009

and by

Exploring Linguistic Features for Web Spam Detection: A Preliminary Study
J Piskorski, M Sydow, D Weiss. Proc of the AIRWeb'08 workshop in conjunction with WWW2008, 2008

and by

Cleaning Search Results using Term Distance Features
J Attenberg, T Suel - Proc of the AIRWeb'08 workshop in conjunction with WWW2008, 2008

and by

Improving Spamdexing Detection Via a Two-Stage Classification Strategy
GG Geng, CH Wang, QD Li - Information Retrieval Technology: 4th Asia Information …, 2008 - Springer

Balázs Rácz, Csaba István Sidló, András Lukács, András A Benczúr,

Two-Phase Data Warehouse Optimized for Data Mining,

In Proc BIRTE workhop in conjunction with VLDB 2006.


A. A. Benczúr, Karoly Csalogany, Miklos Kurucz, Andras Lukacs, Laszlo Lukacs

Sociodemographic Exploration of Telecom Communities.

NSF US-Hungarian Workshop on Large Scale Random Graphs Methods for Modeling Mesoscopic Behavior in Biological and Physical Systems, 2006.

A. A. Benczúr, K. Csalogány, T. Sarlós


Similarity Search to Fight Web Spam.

In Proc. Airweb 2006 in conjunction with SIGIR 2006.

is cited by (12)

Jöran Beel, Bela Gipp, Erik Wilde: Academic Search Engine Optimization (ASEO). Journal of Scholarly Publishing, Vol. 41, No. 2. (1 January 2010), pp. 176-190.

and by

Jacob Abernethy, Olivier Chapelle, and Carlos Castillo. 2010. Graph regularization methods for Web spam detection. Mach. Learn. 81, 2 (November 2010), 207-225.

and by

Kyumin Lee, James Caverlee, and Steve Webb. 2010. Uncovering social spammers: social honeypots + machine learning. In Proceeding of the 33rd international ACM SIGIR conference on Research and development in information retrieval (SIGIR '10). ACM, New York, NY, USA, 435-442.

and by

Akira Yamada, Hara Masanori, Yutaka Miyake, "Web Tracking Site Detection Based on Temporal Link Analysis," Advanced Information Networking and Applications Workshops, International Conference on, pp. 626-631, 2010 IEEE 24th International Conference on Advanced Information Networking and Applications Workshops, 2010.

and by

Fogelman-Soulie, F. and others, Fighting Web Spam, Mining Massive Data Sets for Security: Advances in Data Mining, Search, Social Networks and Text Mining, and Their Applications to Security, 2008.

and by

Improving web spam classifiers using link structure
Q Gan, T Suel In Proc. Airweb 2007 in conjunction with WWW 2007

and by

A large-scale study of link spam detection by graph algorithms
H Saito, M Toyoda, M Kitsuregawa, K Aihara. In Proc. Airweb 2007 in conjunction with WWW 2007

and by

Unsupervised Spam Detection Based on String Alienness Measures


K Narisawa, H Bannai, K Hatano, M Takeda - Lecture Notes in Computer Science Volume 4755 Discovery Science, 2007

and by

Tracking Web spam with HTML style similarities

T Urvoy, E Chauveau, P Filoche, T Lavergne - ACM Transactions on the Web (TWEB) 2008

and by

Boosting the Performance of Web Spam Detection with Ensemble Under-Sampling Classification
GG Geng, CH Wang, QD Li, L Xu, XB Jin - Fuzzy Systems and Knowledge Discovery, 2007

and by

C Castillo, D Donato, A Gionis, V Murdock, F Silvestri

Know your Neighbors: Web Spam Detection using the Web Topology

Submitted for publication, November 2006

and by

C Castillo, D Donato, L Becchetti, P Boldi, M Santini, S Vigna

A Reference Collection for Web Spam

ACM SIGIR Forum, Volume 40, Issue 2, Pages 11-24, December 2006

Péter Schönhofen, András A. Benczúr: Exploiting extremely rare features in text categorization. In Proc ECML/PKDD 2006.

is cited by

Does SVM Really Scale Up to Large Bag of Words Feature Spaces?
F Colas, P Paclik, JN Kok, P Brazdil - Advances in Intelligent Data Analysis, LECTURE NOTES IN COMPUTER SCIENCE, 2007

András A. Benczúr, István Bíró, Károly Csalogány, Máté Uher: Detecting Nepotistic Links by Language Model Disagreement. Proceedings of WWW2006, poster section.

is cited by

Lourdes Araujo and Juan Martinez-Romo. 2010. Web spam detection: new classification features based on qualified link analysis and language models. Trans. Info. For. Sec. 5, 3 (September 2010), 581-590.


and by

Martinez-Romo, J., Web spam identification through language model analysis,

Proceedings of the 5th International Workshop on Adversarial Information Retrieval on the Web, pp 21-28, 2009, ACM New York, NY, USA

and by

A reference collection for web spam
C Castillo, D Donato, L Becchetti, P Boldi, S Vigna - ACM SIGIR Forum, 2006

and by

Measuring similarity to detect qualified links

X Qi, L Nie, BD Davison - Proceedings of the 3rd international AIRWeb workshop, 2007

Tamás Sarlós, András A. Benczúr, Károly Csalogány, Dániel Fogaras, Balázs Rácz: To Randomize or Not To Randomize: Space Optimal Summaries for Hyperlink Analysis. In the Proceedings of WWW2006.

is cited by (16)

Chen Chen, Cindy X. Lin, Matt Fredrikson, Mihai Christodorescu, Xifeng Yan, and Jiawei Han. 2009. Mining graph patterns efficiently via randomized summaries. Proc. VLDB Endow. 2, 1 (August 2009), 742-753.

and by

Rebecca S. Wills and Ilse C. F. Ipsen. 2009. Ordinal Ranking for Google's PageRank. SIAM J. Matrix Anal. Appl. 30, 4 (January 2009), 1677-1696

and by

Purnamrita Sarkar and Andrew W. Moore. 2010. Fast nearest-neighbor search in disk-resident graphs. In Proceedings of the 16th ACM SIGKDD international conference on Knowledge discovery and data mining (KDD '10). ACM, New York, NY, USA, 513-522.

and by

Chen, C. and Lin, C.X. and Fredrikson, M. and Christodorescu, M. and Yan, X. and Han, J. Mining Large Information Networks by Graph Summarization. Link Mining: Models, Algorithms, and Applications, pp. 475-501, 2010, Springer

and by

Andersen, R. and Borgs, C. and Chayes, J. and Hopcroft, J. and Mirrokni, V. and Teng, S.H., Local computation of PageRank contributions, Internet Mathematics 5(1), pp 23-45, 2009


and by

Wills, R.S. and Ipsen, I.C.F., Ordinal ranking for Google’s PageRank, SIAM J. Matrix Anal. Appl, 30(4), pp 1677-1696, 2009

and by

Andersen, R. and Chung, F. and Lang, K., Local partitioning for directed graphs using PageRank, Internet Mathematics 5(1), pp 3-22, 2009

and by

Dou, Z. and Song, R. and Wen, J. and Yuan, X., Evaluating the Effectiveness of Personalized Web Search, IEEE Transactions on Knowledge and Data Engineering 21(8), pp 1178-1190, 2009

and by

Robust PageRank and Locally Computable Spam Detection Features
R Andersen, C Borgs, J Chayes, J Hopcroft, K Jain, Proc of the AIRWeb'08 workshop in conjunction with WWW2008, 2008

and by

Snaket: A Personalized Search-result Clustering Engine

P Ferragina, A Gullì - Journal for the ATI (Asociación de Técnicos de Informática). Invited paper, 2007

and by

Approximating Personalized PageRank with Minimal Use of Web Graph Data

D Gleich, M Polito - Internet Mathematics, 2006

and by

Local Partitioning for Directed Graphs Using PageRank - ►ucsd.edu [PDF]

R Andersen, F Chung, K Lang - LECTURE NOTES IN COMPUTER SCIENCE, Volume 4863/2007

Algorithms and Models for the Web-Graph, 2007

and by

Estimating PageRank on graph streams

AD Sarma, S Gollapudi, R Panigrahy - Proceedings of the twenty-seventh ACM SIGMOD-SIGACT-SIGART symposium on Principles of database systems, 2008

and by

Local Computation of PageRank Contributions, Andersen, R. and Borgs, C. and Chayes, J. and Hopcraft, J. and Mirrokni, V.S. and Teng, S., LECTURE NOTES IN COMPUTER SCIENCE Volume 4863, 2007.


and by

Personalized query expansion for the web
PA Chirita, CS Firan, W Nejdl - Proceedings of the 30th annual international ACM SIGIR 2007

and by

C Kohlschütter, P-A Chirita, and W Nejdl

Using Link Analysis to Identify Aspects in Faceted Web Search

In Proceedings of the SIGIR 2006 Workshop on Faceted Search,

Seattle, WA, USA, August 2006.


András A. Benczúr, Péter Schönhofen: Feature selection based on word-sentence relation. In Proc. ICMLA 2005.

András A. Benczúr, Károly Csalogány, Kata Hum, András Lukács, Balázs Rácz, Csaba István Sidló, Máté Uher: Architecture for mining massive web logs with experiments. In Proceedings of the HUBUSKA Open Workshop on Generic Issues of Knowledge Technologies, 2005.

András A. Benczúr, Károly Csalogány, Tamás Sarlós, Máté Uher: SpamRank – Fully Automatic Link Spam Detection. In Proc. AIRWeb'05 workshop in conjunction with WWW2005.

András A. Benczúr, Károly Csalogány, Tamás Sarlós: On the Feasibility of Low-rank Approximation for Personalized PageRank. Poster Section of WWW2005.

is cited by (3)

A unifying framework of rating users and data items in peer-to-peer and social networks
D Bickson, D Malkhi - Peer-to-Peer Networking and Applications, 2008

and by

Supporting intelligent Web search
M Coyle, B Smyth - ACM Transactions on Internet Technology (TOIT) 2007

and by

Peer-to-Peer Rating

D Bickson, D Malkhi, L Zhou - Proceedings of the Seventh IEEE International Conference on Peer-to-Peer Computing, 2007


Végh, L., Benczúr, A.A.
Primal-dual approach for directed vertex connectivity augmentation and generalizations
Proc 16th ACM-SIAM Symp. on Discrete Algorithms, pp. 500-509. (2005)

Is cited by: see journal version


Benczúr, A.A., Glasser, U, Lukovszki, T
Formal description of a distributed location service for mobile ad hoc networks
Proceedings of the ASM 2003 International Conference on Abstract State Machines, 2003. LNCS volume

is cited by


Roozbeh Farahbod, Extending and Refining an Abstract Operational Semantics of the Web Services Architecture for the Business Process Execution Language, June 2004. Faculty of Applied Sciences, Simon Fraser University


Benczúr, A.A., Csalogány, K, Fogaras, D, Friedman, E, Sarlós, T, Uher, M, Windhager, E
Searching a small national domain -Preliminary Report
WWW2003 Conference, 2003, Budapest

is cited by (10)

Katona, Z. and Sarvary, M.,Network formation and the structure of the commercial world wide web, Marketing Science 27(5), pp 764-787, 2008

and by

EusBila, a search service designed for the agglutinative nature of Basque
I Leturia, A Gurrutxaga, N Areta, I Alegria, A … - Improving Non English Web Searching (iNEWS’07)

and by

C Castillo

Effective Web Crawling

ACM SIGIR Forum, Volume 39, Issue 1, Pages 55-56, June 2005

and by

C Castillo

Effective Web Crawling

PhD thesis, University of Chile, 2004

and by

R Baeza-Yates, C Castillo, and V Lopez

Characteristics of the Web of Spain

International Journal of Scientometrics, Informetrics and Bibliometrics

VOLUME 9 (2005): ISSUE 1. PAPER 3

and by

R Baeza-Yates, C Castillo, and V López

Características de la Web de España (in Spanish)


El Profesional de la Información, Vol. 15, No. 1. January-February,

pp. 6-17 2006.

and by

L Becchetti, C Castillo, D Donato, and A Fazzone

A Comparison of Sampling Techniques for Web Characterization

In Proceedings of the Workshop on Link Analysis (LinkKDD) held in conjunction

with KDD-2006, Philadelphia, USA, August 2006. ACM Press

and by

Zs Katona

Width of a scale-free tree

Journal of Applied Probability 42 (3): 839-850 September 2005

and by

Zs Katona

Levels of a scale-free tree

Random Structures and Algorithms

Volume 29, Issue 2, Pages 194 - 207, 2006

and by

Zs Katona and M Sárváry

Network Formation and the Structure of the Commercial World Wide Web

INSEAD Working Paper 2006/04/MKT, 2006

presented at the

SICS 2006 Summer Institute in Competitive Strategy

Haas School of Business, University of California, Berkeley

28 June 2006


Benczúr, A.A., Fülöp, O
Fast algorithms for even/odd mincuts and generalizations
Proc. European Symp. Alg., Springer Lecture Notes in Computer Science 1879, pp. 88-99 (2000)

is cited by

Detecting symmetries by branch & cut

C Buchheim, M Jünger - Mathematical Programming, 2003

Benczúr, A., Förster, J, Király, Z
Dilworth's Theorem and its application for path systems of a cycle-implementation and analysis
Proc. European Symp. Alg., Springer Lecture Notes in Computer Science 1643:598--509 (1999)

is cited by

Fox, J. and Pach, J., A bipartite analogue of Dilworth’s theorem for multiple partial orders, European Journal of Combinatorics 30(8) pp 1846-1853, 2009, Elsevier

and by

A Bipartite Analogue of Dilworth's Theorem


J Fox, Order, Volume 23, Numbers 2-3, August 2006 , pp. 197-209(13)


and by

All-Pairs Ancestor Problems in Weighted Dags
M Baumgart, S Eckhardt, J Griebsch, S Kosub

and by

Alternating Paths along Axis-Parallel Segments
CD Tóth - Graphs and Combinatorics, 2006

Benczúr, A.A., Karger, D.R.
Augmenting undirected edge-connectivity in O(n2) time
Proc. 9th ACM-SIAM Symp. on Discrete Algorithms, pp. 500-509 (1998)

is cited by: see journal version


Benczúr, A. A., Karger, D. R.
Approximating s-t minimum cuts in O(n2) time
Proc. 28th Annual ACM Symp. on Theory of Comp., pp. 47-55. (1996)

is cited by (34)


F. Thomson Leighton and Ankur Moitra. 2010. Extensions and limits to vertex sparsification. In Proceedings of the 42nd ACM symposium on Theory of computing (STOC '10). ACM, New York, NY, USA, 47-56.

and by

Chechik, S. and Emek, Y. and Patt-Shamir, B. and Peleg, D. Sparse Reliable Graph Backbones. Automata, Languages and Programming, pp. 261-272, 2010

J and by

onah Sherman . Breaking the Multicommodity Flow Barrier for O(vlog n)-Approximations to Sparsest Cut. In Proceedings of the 2009 50th Annual IEEE Symposium on Foundations of Computer Science.

and by

Alexandra Kolla, Yury Makarychev, Amin Saberi, and Shang-Hua Teng. 2010. Subgraph sparsification and nearly optimal ultrasparsifiers. In Proceedings of the 42nd ACM symposium on Theory of computing (STOC '10). ACM, New York, NY, USA, 57-66.

and by

Teng, S.H. The Laplacian Paradigm: Emerging Algorithms for Massive Graphs.

Theory and Applications of Models of Computation, pp. 2-14, 2010


and by

Spielman, D.A., Algorithms, Graph Theory, and Linear Equations in Laplacian Matrices. Proceedings of the International Congress of Mathematicians, 2010

and by


Graph partitioning using single commodity flows, Khandekar, R. and Rao, S. and Vazirani, U., Journal of the ACM (JACM), 56(4), 2009

and by

Goyal, N. and Rademacher, L. and Vempala, S., Expanders via random spanning trees, Proceedings of the Nineteenth Annual ACM-SIAM Symposium on Discrete Algorithms, pp 576-585, 2009

and by

Batson, J.D. and Spielman, D.A. and Srivastava, N., Twice-ramanujan sparsifiers, Proceedings of the 41st annual ACM symposium on Symposium on theory of computing, pp 255-262, 2009

and by

Graph sparsification in the semi-streaming model, Ahn, K.J. and Guha, S., Proceedings of the 36th Internatilonal Collogquium on Automata, Languages and Programming: Part II, 2009

and by

Sarma, A.D. and Gollapudi, S. and Panigrahy, R., Sparse Cut Projections in Graph Streams, Algorithms-ESA 2009: 17th Annual European Symposium, Copenhagen, Denmark, September 7-9

and by

Twice-Ramanujan Sparsifiers
J Batson, DA Spielman, N Srivastava - Arxiv preprint arXiv:0808.0163, 2008

and by

Efficient algorithms for computing all low stedge connectivities and related problems

R Hariharan, T Kavitha, D Panigrahi – Proc STOC 2007

and by

Spectral Sparsification of Graphs
DA Spielman, SH Teng - Arxiv preprint arXiv:0808.4134, 2008

and by

Expanders via Random Spanning Trees

N Goyal, L Rademacher, S Vempala - Arxiv preprint arXiv:0807.1496, 2008


and by

Finding Sparse Cuts Locally Using Evolving Sets
R Andersen, Y Peres - Arxiv preprint arXiv:0811.3779, 2008

and by

Fast edge splitting and Edmonds' arborescence construction for unweighted graphs
A Bhalgat, R Hariharan, T Kavitha, D Panigrahi, STOC 2008

and by

Graph sparsification by effective resistances
DA Spielman, N Srivastava, STOC 2008

and by

A combinatorial, primal-dual approach to semidefinite programs

Arora, S. and Kale, S., Proceedings of the thirty-ninth annual ACM symposium on Theory of computing, 227-236, 2007

and by

Rohit Khandekar, Satish Rao , Umesh Vazirani

Graph partitioning using single commodity flows

Proceedings of the thirty-eighth annual ACM symposium on Theory of computing

Pages: 385 - 390

Year of Publication: 2006

ISBN:1-59593-134-1


and by


Steve Hanneke

An analysis of graph cut size for transductive learning

Proceedings of the 23rd international conference on Machine learning

Pittsburgh, Pennsylvania

Pages: 393 - 399

Year of Publication: 2006

ISBN:1-59593-383-2


and by

DA Spielman, SH Teng, AT Inc, Nearly-Linear Time Algorithms for Graph Partitioning, Graph Sparsification, and Solving Linear Programs Arxiv preprint cs.DS/0310051 (2003)

and by

PA Tucker, TC Hu, MT Shing, Min Cuts Without Path Packing Tech. Report CS99-625, Computer Science Dept. UCSD

and by

X Wu, DZ Chen, JJ Mason, SR Schmid, Pairwise Data Clustering and Applications Lecture Notes in Computer Science, Vol. 2697, Springer Verlag, Proc of the 9th International Computing and Combinatorics Conference (COCOON), Big Sky, MT, USA, July 25-28, 2003, pp.455-466



and by

R. Kannan, S. Vempala, and A. Vetta, On Clusterings. Good, Bad and Spectral 41st Annual Symposium on Foundations of Computer Science 12-14 November, 2000 Redondo Beach, California


and by

Asano T, Asano Y, Recent developments in maximum flow algorithms, J OPER RES SOC JPN 43: (1) 2-31 MAR 2000


and by

Andrew Goldberg, Recent developments in Maximum Flow Algorithms, TR \#98-045 NEC Research Institute


and by

Goldberg AV Recent developments in maximum flow algorithms (invited lecture) LECT NOTES COMPUT SC 1432: 1-10 1998


and by

Andrew Goldberg, Satish Rao Length Functions for Flow Computations, TR \#97-055 NEC Research Institute


and by

Leighton T, Rao S, Multicommodity max-flow min-cut theorems and their use in designing approximation algorithms, J ACM 46: (6) 787-832 NOV 1999


and by

Feige, Krauthgamer, Nissim, Approximating the minimum bisection size, STOC 2000


and by

Feige, Krauthgamer, A polylogarithmic approximation of the minimum bisection size, FOCS 2000


and by

Guy Even, Joseph (Seffi) Naor, and Leonid Zosin. An 8-approximation algorithm for the subset feedback vertex set problem. In 37th Annual Symposium on Foundations of Computer Science, pages 310-319, Burlington, Vermont, 14-16 October 1996. IEEE.


and by

Andrew V. Goldberg and Satish Rao. Beyond the flow decomposition barrier. In 38th Annual Symposium on Foundations of Computer Science, pages 2-11, Miami Beach, Florida, 20-22 October 1997. IEEE.


Benczúr, A.A.
A representation of cuts within 6/5 times the edge connectivity with applications
Proc. 34th Annual Symp. on Found. of Comp. Sci., pp. 92—102. (1995)

is cited by (6)

Toth CD Alternating paths along orthogonal segments LECT NOTES COMPUT SC 2748: 389-400 2003



and by

Nagamochi H, Nakamura S, Ishii T, Constructing a cactus for minimum cuts of a graph in O (mn+n(2) log n) time and O(m) Space IEICE T INF SYST E86D (2): 179-185 FEB 2003


and by

Oded Goldreich and Dana Ron. Property testing in bounded degree graphs.

Algorithmica 32 (2):302-343 (2002)


and by

Dinitz Y, Nossenson R Incremental maintenance of the 5-edge-connectivity classes of a graph LECT NOTES COMPUT SC 1851: 272-285 2000


and by

Denis Naddef, Stefan Thienel, Efficient Separation Routines for the Symmetric Traveling Salesman Problem I: General Tools and Comb Separation www-apache.imag.fr/