@inproceedings{conf/cikm/DingFJPCPRDS04,
  author = {Ding, Li and Finin, Timothy W. and Joshi, Anupam and Pan, Rong and Cost, R. Scott and Peng, Yun and Reddivari, Pavan and Doshi, Vishal and Sachs, Joel},
  booktitle = {CIKM},
  ee = {http://doi.acm.org/10.1145/1031289},
  interhash = {17031c743c455bf9de56e142d727dbb7},
  intrahash = {ab5c85d78daba236ca1bb5ad49865ee5},
  pages = {652-659},
  title = {Swoogle: a search and metadata engine for the semantic web.},
  url = {http://dblp.uni-trier.de/db/conf/cikm/cikm2004.html#DingFJPCPRDS04},
  year = 2004
}

@inproceedings{Approximating2008Java,
  abstract = {In many social media applications, a small fraction of the members are highly linked while most are sparsely connected to the network. Such a skewed distribution is sometimes referred to as the"long tail". Popular applications like meme trackers and content aggregators mine for information from only the popular blogs located at the head of this curve. On the other hand, the long tail contains large volumes of interesting information and niches. The question we address in this work is how best to approximate the community membership of entities in the long tail using only a small percentage of the entire graph structure. Our technique utilizes basic linear algebra manipulations and spectral methods. It has the advantage of quickly and efficiently finding a reasonable approximation of the community structure of the overall network. Such a method has significant applications in blog analysis engines as well as social media monitoring tools in general. },
  author = {Java, Akshay and Joshi, Anupam and FininBook, Tim},
  booktitle = {Proceedings of the Second International Conference on Weblogs and Social Media(ICWSM 2008)},
  date = {2008 Abstract:},
  interhash = {ede357e110fee8803dc181d262f30087},
  intrahash = {386f36679c111f30e37ced272d5b355c},
  publisher = {AAAI Press},
  title = {Approximating the Community Structure of the Long Tail},
  url = {http://ebiquity.umbc.edu/paper/html/id/381/Approximating-the-Community-Structure-of-the-Long-Tail},
  year = 2008
}

@inproceedings{Detecting_Commmunities_via_Simultaneous_Clustering_of_Graphs_and_Folksonomies,
  author = {Java, Akshay and Joshi, Anupam and Finin, Tim},
  booktitle = {WebKDD 2008 Workshop on Web Mining and Web Usage Analysis},
  interhash = {acfec953843b168e61e2e167e29b4c3d},
  intrahash = {645abd6b3191a2a6e844d7542651ed1c},
  month = {August},
  note = {To Appear},
  title = {Detecting Commmunities via Simultaneous Clustering of Graphs and Folksonomies},
  year = 2008
}

@inproceedings{Java2008,
  abstract = {We present a simple technique for detecting communities by utilizing both the link structure and folksonomy (or tag) information that is readily available in most social media systems. A simple way to describe our approach is by defining a community as a set of nodes in a graph that link more frequently to within this set than outside it and they share similar tags. Our technique is based on the Normalized Cut (NCut) algorithm and can be easily and efficiently implemented. We validate our method by using a real network of blogs and tag information obtained from a social bookmarking site. We also verify our results on a citation network for which we have access to ground truth cluster information. Our method, Simultaneous Cut (SimCut), has the advantage that it can group related tags and cluster the nodes simultaneously.},
  author = {Java, Akshay and Joshi, Anupam and Finin, Tim},
  booktitle = {Proceedings of the Tenth Workshop on Web Mining and Web Usage Analysis (WebKDD)},
  interhash = {acfec953843b168e61e2e167e29b4c3d},
  intrahash = {80e4f692625afcf21e8195915ea93de0},
  month = {August},
  note = {Held in conjunction with The 14th ACM SIGKDD International Conference on Knowledge Discovery and Data Mining (KDD 2008)},
  publisher = {ACM},
  title = {Detecting Commmunities via Simultaneous Clustering of Graphs and Folksonomies},
  url = {http://ebiquity.umbc.edu/paper/html/id/406/Detecting-Commmunities-via-Simultaneous-Clustering-of-Graphs-and-Folksonomies},
  year = 2008
}

@inproceedings{Detecting_Commmunities_via_Simultaneous_Clustering_of_Graphs_and_Folksonomies,
  author = {Java, Akshay and Joshi, Anupam and Finin, Tim},
  booktitle = {WebKDD 2008 Workshop on Web Mining and Web Usage Analysis},
  interhash = {acfec953843b168e61e2e167e29b4c3d},
  intrahash = {645abd6b3191a2a6e844d7542651ed1c},
  month = {August},
  note = {To Appear},
  title = {Detecting Commmunities via Simultaneous Clustering of Graphs and Folksonomies},
  year = 2008
}

@inproceedings{Detecting_Commmunities_via_Simultaneous_Clustering_of_Graphs_and_Folksonomies,
  author = {Java, Akshay and Joshi, Anupam and Finin, Tim},
  booktitle = {WebKDD 2008 Workshop on Web Mining and Web Usage Analysis},
  interhash = {acfec953843b168e61e2e167e29b4c3d},
  intrahash = {645abd6b3191a2a6e844d7542651ed1c},
  month = {August},
  note = {To Appear},
  title = {{Detecting Commmunities via Simultaneous Clustering of Graphs and Folksonomies}},
  year = 2008
}

@inproceedings{Approximating2008Java,
  abstract = {In many social media applications, a small fraction of the members are highly linked while most are sparsely connected to the network. Such a skewed distribution is sometimes referred to as the"long tail". Popular applications like meme trackers and content aggregators mine for information from only the popular blogs located at the head of this curve. On the other hand, the long tail contains large volumes of interesting information and niches. The question we address in this work is how best to approximate the community membership of entities in the long tail using only a small percentage of the entire graph structure. Our technique utilizes basic linear algebra manipulations and spectral methods. It has the advantage of quickly and efficiently finding a reasonable approximation of the community structure of the overall network. Such a method has significant applications in blog analysis engines as well as social media monitoring tools in general. },
  author = {Java, Akshay and Joshi, Anupam and FininBook, Tim},
  booktitle = {Proceedings of the Second International Conference on Weblogs and Social Media(ICWSM 2008)},
  date = {2008 Abstract:},
  interhash = {ede357e110fee8803dc181d262f30087},
  intrahash = {386f36679c111f30e37ced272d5b355c},
  publisher = {AAAI Press},
  title = {Approximating the Community Structure of the Long Tail},
  url = {http://ebiquity.umbc.edu/paper/html/id/381/Approximating-the-Community-Structure-of-the-Long-Tail},
  year = 2008
}

@inproceedings{DBLP:conf/semweb/DingPFJPK05,
  author = {Ding, Li and Pan, Rong and Finin, Timothy W. and Joshi, Anupam and Peng, Yun and Kolari, Pranam},
  bibsource = {DBLP, http://dblp.uni-trier.de},
  booktitle = {International Semantic Web Conference},
  crossref = {DBLP:conf/semweb/2005},
  ee = {http://dx.doi.org/10.1007/11574620_14},
  interhash = {fbd1c77889dc928ae2c157761d1b5567},
  intrahash = {12ca34d21f87f455fe38ca90c5ddf377},
  pages = {156-170},
  title = {Finding and Ranking Knowledge on the Semantic Web.},
  url = {http://ebiquity.umbc.edu/get/a/publication/197.pdf},
  year = 2005
}

@inproceedings{conf/cikm/DingFJPCPRDS04,
  author = {Ding, Li and Finin, Timothy W. and Joshi, Anupam and Pan, Rong and Cost, R. Scott and Peng, Yun and Reddivari, Pavan and Doshi, Vishal and Sachs, Joel},
  booktitle = {CIKM},
  ee = {http://doi.acm.org/10.1145/1031289},
  interhash = {17031c743c455bf9de56e142d727dbb7},
  intrahash = {ab5c85d78daba236ca1bb5ad49865ee5},
  pages = {652-659},
  title = {Swoogle: a search and metadata engine for the semantic web.},
  url = {http://dblp.uni-trier.de/db/conf/cikm/cikm2004.html#DingFJPCPRDS04},
  year = 2004
}