QuickSearch:   Number of matching entries: 0.

AuthorTitleYearJournal/ProceedingsReftypeDOI/URL
Java, A., Joshi, A. & Finin, T. Detecting Commmunities via Simultaneous Clustering of Graphs and Folksonomies

[BibTeX]

 2008 WebKDD 2008 Workshop on Web Mining and Web Usage Analysis   inproceedings  
BibTeX: 
@inproceedings{Detecting_Commmunities_via_Simultaneous_Clustering_of_Graphs_and_Folksonomies,
  author = {Java, Akshay and Joshi, Anupam and Finin, Tim},
  title = {Detecting Commmunities via Simultaneous Clustering of Graphs and Folksonomies},
  booktitle = {WebKDD 2008 Workshop on Web Mining and Web Usage Analysis},
  year = {2008},
  note = {To Appear}
}
Symeonidis, P., Nanopoulos, A. & Manolopoulos, Y. Tag recommendations based on tensor dimensionality reduction

[BibTeX]

 2008 RecSys '08: Proceedings of the 2008 ACM conference on Recommender systems   inproceedings DOIURL  
BibTeX: 
@inproceedings{1454017,
  author = {Symeonidis, Panagiotis and Nanopoulos, Alexandros and Manolopoulos, Yannis},
  title = {Tag recommendations based on tensor dimensionality reduction},
  booktitle = {RecSys '08: Proceedings of the 2008 ACM conference on Recommender systems},
  publisher = {ACM},
  year = {2008},
  pages = {43--50},
  url = {http://portal.acm.org/citation.cfm?id=1454017},
  doi = {http://doi.acm.org/10.1145/1454008.1454017}
}
Chi, Y., Song, X., Zhou, D., Hino, K. & Tseng, B. L. Evolutionary spectral clustering by incorporating temporal smoothness.

[BibTeX]

 2007 KDD   inproceedings URL  
BibTeX: 
@inproceedings{conf/kdd/ChiSZHT07,
  author = {Chi, Yun and Song, Xiaodan and Zhou, Dengyong and Hino, Koji and Tseng, Belle L.},
  title = {Evolutionary spectral clustering by incorporating temporal smoothness.},
  booktitle = {KDD},
  publisher = {ACM},
  year = {2007},
  pages = {153-162},
  url = {http://dblp.uni-trier.de/db/conf/kdd/kdd2007.html#ChiSZHT07}
}
Du, N., Wu, B., Pei, X., Wang, B. & Xu, L. Community detection in large-scale social networks

[Abstract] [BibTeX]

 2007 WebKDD/SNA-KDD '07: Proceedings of the 9th WebKDD and 1st SNA-KDD 2007 workshop on Web mining and social network analysis   inproceedings DOIURL  
Abstract: Recent years have seen that WWW is becoming a flourishing social media which enables individuals to easily share opinions, experiences and expertise at the push of a single button. With the pervasive usage of instant messaging systems and the fundamental shift in the ease of publishing content, social network researchers and graph theory researchers are now concerned with inferring community structures by analyzing the linkage patterns among individuals and web pages. Although the investigation of community structures has motivated many diverse algorithms, most of them are unsuitable for large-scale social networks because of the computational cost. Moreover, in addition to identify the possible community structures, how to define and explain the discovered communities is also significant in many practical scenarios.
In this paper, we present the algorithm ComTector(Community DeTector) which is more efficient for the community detection in large-scale social networks based on the nature of overlapping communities in the real world. This algorithm does not require any priori knowledge about the number or the original division of the communities. Because real networks are often large sparse graphs, its running time is thus O(C × Tri2), where C is the number of the detected communities and Tri is the number of the triangles in the given network for the worst case. Then we propose a general naming method by combining the topological information with the entity attributes to define the discovered communities. With respected to practical applications, ComTector is challenged with several real life networks including the Zachary Karate Club, American College Football, Scientific Collaboration, and Telecommunications Call networks. Experimental results show that this algorithm can extract meaningful communities that are agreed with both of the objective facts and our intuitions.
BibTeX: 
@inproceedings{1348552,
  author = {Du, Nan and Wu, Bin and Pei, Xin and Wang, Bai and Xu, Liutong},
  title = {Community detection in large-scale social networks},
  booktitle = {WebKDD/SNA-KDD '07: Proceedings of the 9th WebKDD and 1st SNA-KDD 2007 workshop on Web mining and social network analysis},
  publisher = {ACM},
  year = {2007},
  pages = {16--25},
  url = {http://portal.acm.org/citation.cfm?id=1348549.1348552&coll=GUIDE&dl=GUIDE&type=series&idx=SERIES939&part=series&WantType=Proceedings&title=KDD&CFID=17695029&CFTOKEN=22803053},
  doi = {http://doi.acm.org/10.1145/1348549.1348552}
}
Grahl, M., Hotho, A. & Stumme, G. Conceptual Clustering of Social Bookmark Sites

[BibTeX]

 2007 Workshop Proceedings of Lernen - Wissensentdeckung - Adaptivität (LWA 2007)   inproceedings URL  
BibTeX: 
@inproceedings{grahl07conceptualKdml,
  author = {Grahl, Miranda and Hotho, Andreas and Stumme, Gerd},
  title = {Conceptual Clustering of Social Bookmark Sites},
  booktitle = {Workshop Proceedings of Lernen - Wissensentdeckung - Adaptivität (LWA 2007)},
  publisher = {Martin-Luther-Universität Halle-Wittenberg},
  year = {2007},
  pages = {50-54},
  url = {http://www.tagora-project.eu/wp-content/2007/06/grahl_iknow07.pdf }
}
Begelman, G., Keller, P. & Smadja, F. Automated Tag Clustering: Improving search and exploration in the tag space

[BibTeX]

 2006 Proceedings of the WWW 2006 Workshop on Collaborative Web Tagging Workshop   inproceedings URL  
BibTeX: 
@inproceedings{Begelman2006,
  author = {Begelman, Grigory and Keller, Philipp and Smadja, Frank},
  title = {Automated Tag Clustering: Improving search and exploration in the tag space},
  booktitle = {Proceedings of the WWW 2006 Workshop on Collaborative Web Tagging 	Workshop},
  year = {2006},
  url = {http://www.rawsugar.com/www2006/taggingworkshopschedule.html}
}
Newman, M. Finding community structure in networks using the eigenvectors of matrices

[BibTeX]

 2006 Physical Review E   article  
BibTeX: 
@article{newman2006fcs,
  author = {Newman, MEJ},
  title = {{Finding community structure in networks using the eigenvectors of matrices}},
  journal = {Physical Review E},
  publisher = {APS},
  year = {2006},
  volume = {74},
  number = {3},
  pages = {36104}
}
Schmitz, P. Inducing Ontology from Flickr Tags

[Abstract] [BibTeX]

 2006 Proceedings of the Workshop on Collaborative Tagging at WWW2006   inproceedings URL  
Abstract: In this paper, we describe some promising initial results in inducing ontology from the Flickr tag vocabulary, using a subsumption-based model. We describe the utility of faceted ontology as a supplement to a tagging system and present our model and results. We propose a revised, probabilistic model using seed ontologies to induce faceted ontology, and describe how the model can integrate into the logistics of tagging communities.
BibTeX: 
@inproceedings{schmitz06-inducing,
  author = {Schmitz, Patrick},
  title = {Inducing Ontology from Flickr Tags},
  booktitle = {Proceedings of the Workshop on Collaborative Tagging at WWW2006},
  year = {2006},
  url = {http://.citeulike.org/user/ryanshaw/article/740688}
}
Danon, L., Diaz-Guilera, A., Duch, J. & Arenas, A. Comparing community structure identification

[BibTeX]

 2005 Journal of Statistical Mechanics: Theory and Experiment   article  
BibTeX: 
@article{danon2005ccs,
  author = {Danon, L. and Diaz-Guilera, A. and Duch, J. and Arenas, A.},
  title = {{Comparing community structure identification}},
  journal = {Journal of Statistical Mechanics: Theory and Experiment},
  publisher = {Institute of Physics Publishing},
  year = {2005},
  volume = {9},
  pages = {P09008}
}
Newman, M. E. & Girvan, M. Finding and evaluating community structure in networks

[Abstract] [BibTeX]

 2004 Phys Rev E Stat Nonlin Soft Matter Phys   article URL  
Abstract: We propose and study a set of algorithms for discovering community structure in networks-natural divisions of network nodes into densely connected subgroups. Our algorithms all share two definitive features: first, they involve iterative removal of edges from the network to split it into communities, the edges removed being identified using any one of a number of possible "betweenness" measures, and second, these measures are, crucially, recalculated after each removal. We also propose a measure for the strength of the community structure found by our algorithms, which gives us an objective metric for choosing the number of communities into which a network should be divided. We demonstrate that our algorithms are highly effective at discovering community structure in both computer-generated and real-world network data, and show how they can be used to shed light on the sometimes dauntingly complex structure of networked systems.
BibTeX: 
@article{Newman04communityStructure,
  author = {Newman, M E and Girvan, M},
  title = {Finding and evaluating community structure in networks},
  journal = {Phys Rev E Stat Nonlin Soft Matter Phys},
  year = {2004},
  volume = {69},
  number = {2},
  pages = {026113.1-15},
  url = {http://www.ncbi.nlm.nih.gov/pubmed/14995526}
}
Newman, M. Detecting community structure in networks

[BibTeX]

 2004 The European Physical Journal B-Condensed Matter   article  
BibTeX: 
@article{newman2004dcs,
  author = {Newman, MEJ},
  title = {{Detecting community structure in networks}},
  journal = {The European Physical Journal B-Condensed Matter},
  publisher = {Springer},
  year = {2004},
  volume = {38},
  number = {2},
  pages = {321--330}
}
Huang, X. & Lai, W. Identification of clusters in the Web graph based on link topology

[BibTeX]

 2003 Database Engineering and Applications Symposium, 2003. Proceedings. Seventh International   article  
BibTeX: 
@article{1214919,
  author = {Huang, Xiaodi and Lai, Wei},
  title = {Identification of clusters in the Web graph based on link topology},
  journal = {Database Engineering and Applications Symposium, 2003. Proceedings. Seventh International},
  year = {2003},
  pages = { 123-128}
}
Flake, G., Lawrence, S., Giles, C. & Coetzee, F. Self-organization and identification of Web communities

[BibTeX]

 2002 Computer   article  
BibTeX: 
@article{flake2002soa,
  author = {Flake, GW and Lawrence, S. and Giles, CL and Coetzee, FM},
  title = {{Self-organization and identification of Web communities}},
  journal = {Computer},
  year = {2002},
  volume = {35},
  number = {3},
  pages = {66--70}
}
Dhillon, I. S. Co-clustering documents and words using bipartite spectral graph partitioning

[BibTeX]

 2001 KDD '01: Proceedings of the seventh ACM SIGKDD international conference on Knowledge discovery and data mining   inproceedings DOIURL  
BibTeX: 
@inproceedings{coclustering01,
  author = {Dhillon, Inderjit S.},
  title = {Co-clustering documents and words using bipartite spectral graph partitioning},
  booktitle = {KDD '01: Proceedings of the seventh ACM SIGKDD international conference on Knowledge discovery and data mining},
  publisher = {ACM Press},
  year = {2001},
  pages = {269--274},
  url = {http://portal.acm.org/citation.cfm?id=502512.502550},
  doi = {http://dx.doi.org/10.1145/502512.502550}
}
Wagstaff, K., Cardie, C., Rogers, S. & Schrödl, S. Constrained K-means Clustering with Background Knowledge.

[BibTeX]

 2001 ICML   inproceedings URL  
BibTeX: 
@inproceedings{conf/icml/WagstaffCRS01,
  author = {Wagstaff, Kiri and Cardie, Claire and Rogers, Seth and Schrödl, Stefan},
  title = {Constrained K-means Clustering with Background Knowledge.},
  booktitle = {ICML},
  publisher = {Morgan Kaufmann},
  year = {2001},
  pages = {577-584},
  url = {http://dblp.uni-trier.de/db/conf/icml/icml2001.html#WagstaffCRS01}
}
Flake, G. W., Lawrence, S. & Giles, C. L. Efficient identification of Web communities

[BibTeX]

 2000 KDD '00: Proceedings of the sixth ACM SIGKDD international conference on Knowledge discovery and data mining   inproceedings DOI  
BibTeX: 
@inproceedings{347121,
  author = {Flake, Gary William and Lawrence, Steve and Giles, C. Lee},
  title = {Efficient identification of Web communities},
  booktitle = {KDD '00: Proceedings of the sixth ACM SIGKDD international conference on Knowledge discovery and data mining},
  publisher = {ACM Press},
  year = {2000},
  pages = {150--160},
  doi = {http://doi.acm.org/10.1145/347090.347121}
}
Shi, J. & Malik, J. Normalized Cuts and Image Segmentation.

[BibTeX]

 1997 CVPR   inproceedings URL  
BibTeX: 
@inproceedings{conf/cvpr/ShiM97,
  author = {Shi, Jianbo and Malik, Jitendra},
  title = {Normalized Cuts and Image Segmentation.},
  booktitle = {CVPR},
  year = {1997},
  pages = {731-737},
  url = {http://dblp.uni-trier.de/db/conf/cvpr/cvpr1997.html#ShiM97}
}
Berry, M., Dumais, S. & O'Brien, G. Using Linear Algebra for Intelligent Information Retrieval

[BibTeX]

 1995 SIAM REVIEW   article  
BibTeX: 
@article{berry1995ula,
  author = {Berry, M.W. and Dumais, S.T. and O'Brien, G.W.},
  title = {{Using Linear Algebra for Intelligent Information Retrieval}},
  journal = {SIAM REVIEW},
  publisher = {SIAM SOCIETY FOR INDUSTRIAL AND APPLIED},
  year = {1995},
  volume = {37},
  pages = {573--595}
}
Chan, P. K., Schlag, M. D. F. & Zien, J. Y. Spectral K-way ratio-cut partitioning and clustering.

[BibTeX]

 1994 IEEE Trans. on CAD of Integrated Circuits and Systems   article URL  
BibTeX: 
@article{journals/tcad/ChanSZ94,
  author = {Chan, Pak K. and Schlag, Martine D. F. and Zien, Jason Y.},
  title = {Spectral K-way ratio-cut partitioning and clustering.},
  journal = {IEEE Trans. on CAD of Integrated Circuits and Systems},
  year = {1994},
  volume = {13},
  number = {9},
  pages = {1088-1096},
  url = {http://dblp.uni-trier.de/db/journals/tcad/tcad13.html#ChanSZ94}
}
Fiedler, M. Algebraic connectivity of graphs

[BibTeX]

 1973 Czechoslovak Mathematical Journal   article  
BibTeX: 
@article{fiedler1973acg,
  author = {Fiedler, M.},
  title = {{Algebraic connectivity of graphs}},
  journal = {Czechoslovak Mathematical Journal},
  year = {1973},
  volume = {23},
  number = {98},
  pages = {298--305}
}

Created by JabRef export filters on 01/05/2024 by the social publication management platform PUMA