@article{1751-8121-41-22-224016,
  abstract = {We analyze CiteULike, an online collaborative tagging system where users bookmark and annotate scientific papers. Such a system can be naturally represented as a tri-partite graph whose nodes represent papers, users and tags connected by individual tag assignments. The semantics of tags is studied here, in order to uncover the hidden relationships between tags. We find that the clustering coefficient can be used to analyze the semantical patterns among tags.},
  author = {Capocci, Andrea and Caldarelli, Guido},
  interhash = {14c8ecbc38dcdae876c3f4401006e3bb},
  intrahash = {2a219a2664c566b405420f720583643a},
  journal = {Journal of Physics A: Mathematical and Theoretical},
  number = 22,
  pages = {224016 (7pp)},
  title = {Folksonomies and clustering in the collaborative system CiteULike},
  url = {http://stacks.iop.org/1751-8121/41/224016},
  volume = 41,
  year = 2008
}

@inproceedings{xin2008www,
  abstract = {The success and popularity of social network systems, such as del.icio.us, Facebook, MySpace, and YouTube, have generated many interesting and challenging problems to the research community. Among others, discovering social interests shared by groups of users is very important because it helps to connect people with common interests and encourages people to contribute and share more contents. The main challenge to solving this problem comes from the diffi- culty of detecting and representing the interest of the users. The existing approaches are all based on the online connections of users and so unable to identify the common interest of users who have no online connections. In this paper, we propose a novel social interest discovery approach based on user-generated tags. Our approach is motivated by the key observation that in a social network, human users tend to use descriptive tags to annotate the contents that they are interested in. Our analysis on a large amount of real-world traces reveals that in general, user-generated tags are consistent with the web content they are attached to, while more concise and closer to the understanding and judgments of human users about the content. Thus, patterns of frequent co-occurrences of user tags can be used to characterize and capture topics of user interests. We have developed an Internet Social Interest Discovery system, ISID, to discover the common user interests and cluster users and their saved URLs by different interest topics. Our evaluation shows that ISID can effectively cluster similar documents by interest topics and discover user communities with common interests no matter if they have any online connections.},
  author = {Li, Xin and Guo, Lei and Zhao, Yihong E.},
  booktitle = {Proceedings of the 17th International World Wide Web Conference},
  interhash = {d7e6a5b8d215682b2a75add69c01de29},
  intrahash = {42b4c94cff05ccef031235d661a7a77a},
  pages = {675-684},
  publisher = {ACM},
  title = {Tag-based Social Interest Discovery},
  url = {http://www2008.org/papers/pdf/p675-liA.pdf},
  year = 2008
}

@inproceedings{salton1988spreading,
  abstract = {Spreading activation methods have been recommended in information retrieval to expand the search vocabulary and to complement the retrieved document sets. The spreading activation strategy is reminiscent of earlier associative indexing and retrieval systems. Some spreading activation procedures are briefly described, and evaluation output is given, reflecting the effectiveness of one of the proposed procedures.},
  address = {New York, NY, USA},
  author = {Salton, G. and Buckley, C.},
  booktitle = {SIGIR '88: Proceedings of the 11th annual international ACM SIGIR conference on Research and development in information retrieval},
  doi = {http://doi.acm.org/10.1145/62437.62447},
  interhash = {7fdb31627e1a45ce109c7245fb6462b9},
  intrahash = {994aef0486e69095ee0d8ba5b3e3a91c},
  isbn = {2-7061-0309-4},
  location = {Grenoble, France},
  pages = {147--160},
  publisher = {ACM Press},
  title = {On the use of spreading activation methods in automatic information},
  url = {http://portal.acm.org/citation.cfm?id=62447&dl=ACM&coll=GUIDE},
  year = 1988
}

@article{crestani1997spreading,
  abstract = {This paper surveys the use of Spreading Activation techniques onSemantic Networks in Associative Information Retrieval. The majorSpreading Activation models are presented and their applications toIR is surveyed. A number of works in this area are criticallyanalyzed in order to study the relevance of Spreading Activation forassociative IR.
ER  -},
  author = {Crestani, F.},
  interhash = {3dfe398bb588335ffc562088d5a509de},
  intrahash = {c26c16e0a8036000b788fada656f59dd},
  journal = {Artificial Intelligence Review},
  month = {December},
  number = 6,
  pages = {453--482},
  title = {Application of Spreading Activation Techniques in Information Retrieval},
  url = {http://dx.doi.org/10.1023/A:1006569829653},
  volume = 11,
  year = 1997
}

@inproceedings{HWLK06,
  author = {Han, Peng and Wang, Zhimei and Li, Zhiyun and Kramer, Bernd and Yang, Fan},
  booktitle = {Web Intelligence},
  crossref = {conf/webi/2006},
  date = {2007-01-10},
  ee = {http://doi.ieeecomputersociety.org/10.1109/WI.2006.162},
  interhash = {caf35361720e0ccb4aa74169646cc606},
  intrahash = {b652b0d73b964ebc282c3c3060c01c9d},
  isbn = {0-7695-2747-7},
  pages = {757-760},
  publisher = {IEEE Computer Society},
  title = {Substitution or Complement: An Empirical Analysis on the Impact of Collaborative Tagging on Web Search.},
  url = {http://dblp.uni-trier.de/db/conf/webi/webi2006.html#HanWLKY06},
  year = 2006
}