%0 Conference Paper %1 citeulike:344959 %A Flake, Gary W. %A Lawrence, Steve %A Giles, Lee C. %B KDD '00: Proceedings of the sixth ACM SIGKDD international conference on Knowledge discovery and data mining %C New York, NY, USA %D 2000 %I ACM Press %K community sna %P 150--160 %R 10.1145/347090.347121 %T Efficient identification of Web communities %U http://dx.doi.org/10.1145/347090.347121 %@ 1581132336

@inproceedings{citeulike:344959, added-at = {2006-09-25T12:54:00.000+0200}, address = {New York, NY, USA}, author = {Flake, Gary W. and Lawrence, Steve and Giles, Lee C.}, biburl = {https://www.bibsonomy.org/bibtex/213be2236eafd36523e2bda5fe645aab4/grahl}, booktitle = {KDD '00: Proceedings of the sixth ACM SIGKDD international conference on Knowledge discovery and data mining}, citeulike-article-id = {344959}, comment = {Main.ThomasHofmannCiteSeer --- Data: WWW Domain: support web-crawlers/search engines Task: find communities of web pages that are highly inter-linked Method: Use max-flow-min-cut on a set of web pages that are linked to a virtual sink (e). The set is obtained from a set of seed-pages (b) that may be augmented via an EM procedure, (which are all linked to a virtual source (a)) plus all in/out links (c) + all outlinks (d) Rating: 4/5 --- This method should be tried on scientific paper-graphs --- max-flow min cut. Find right number of seed pages with EM-Algo (?)}, doi = {10.1145/347090.347121}, interhash = {fe87690693bc84a663c00371684da561}, intrahash = {13be2236eafd36523e2bda5fe645aab4}, isbn = {1581132336}, keywords = {community sna}, pages = {150--160}, priority = {0}, publisher = {ACM Press}, timestamp = {2007-07-25T11:36:55.000+0200}, title = {Efficient identification of Web communities}, url = {http://dx.doi.org/10.1145/347090.347121}, year = 2000 }