@techreport{ilprints750,
  abstract = {The original PageRank algorithm for improving the ranking of search-query results computes a single vector, using the link structure of the Web, to capture the relative ``importance'' of Web pages, independent of any particular search query. To yield more accurate search results, we propose computing a {\em set} of PageRank vectors, biased using a set of representative topics, to capture more accurately the notion of importance with respect to a particular topic.  For ordinary keyword search queries, we compute the topic-sensitive PageRank scores for pages satisfying the query using the topic of the query keywords.  For searches done in context (e.g., when the search query is performed by highlighting words in a Web page), we compute the topic-sensitive PageRank scores using the topic of the context in which the query appeared.  By using linear combinations of these (precomputed) biased PageRank vectors to generate context-specific importance scores for pages at query time, we show that we can generate more accurate rankings than with a single, generic PageRank vector. },
  author = {Haveliwala, Taher H.},
  institution = {Stanford InfoLab},
  interhash = {959ab9af6c35acb5d8513fa032620ba7},
  intrahash = {34aedd24fc7a45f189be1ca70dfd99e2},
  journal = {IEEE Transactions on Knowledge and Data Engineering},
  note = {Extended version of the WWW2002 paper on Topic-Sensitive PageRank.},
  number = {2003-29},
  publisher = {Stanford InfoLab},
  title = {Topic-Sensitive PageRank: A Context-Sensitive Ranking Algorithm for Web Search},
  type = {Technical Report},
  url = {http://ilpubs.stanford.edu:8090/750/},
  year = 2003
}

@inproceedings{abel2009contextbased,
  abstract = {With the advent of Web 2.0 tagging became a popular feature. People tag diverse kinds of content, e.g. products at Amazon, music at Last.fm, images at Flickr, etc. Clicking on a tag enables the users to explore related content. In this paper we investigate how such tag-based queries, initialized by the clicking activity, can be enhanced with automatically produced contextual information so that the search result better fits to the actual aims of the user. We introduce the SocialHITS algorithm and present an experiment where we compare different algorithms for ranking 
users, tags, and resources in a contextualized way.},
  address = {New York, NY, USA},
  author = {Abel, Fabian and Baldoni, Matteo and Baroglio, Cristina and Henze, Nicola and Krause, Daniel and Patti, Viviana},
  booktitle = {HT '09: Proceedings of the Twentieth ACM Conference on Hypertext and Hypermedia},
  interhash = {0e0dff0c21fd77d2d1f0224317c4974f},
  intrahash = {17d5c35426963e20875ec1dc42913855},
  month = {July},
  paperid = {fp060},
  publisher = {ACM},
  session = {Full Paper},
  title = {Context-based Ranking in Folksonomies},
  year = 2009
}

@article{10.1109/WI.2007.108,
  address = {Los Alamitos, CA, USA},
  author = {Nauman, Mohammad and Khan, Shahbaz},
  doi = {http://doi.ieeecomputersociety.org/10.1109/WI.2007.108},
  interhash = {ed3957694fe4ccb1137780c720b7d79a},
  intrahash = {799817443dab31b534315a790c24a9f6},
  isbn = {0-7695-3026-5},
  journal = {wi},
  pages = {423-426},
  publisher = {IEEE Computer Society},
  title = {Using PersonalizedWeb Search for Enhancing Common Sense and Folksonomy Based Intelligent Search Systems},
  volume = 0,
  year = 2007
}

@article{sinclair:ftc,
  author = {Sinclair, J. and Cardew-Hall, M.},
  interhash = {fe7fb4aad79ca5ee3ba8a5b2e1c3cd5b},
  intrahash = {539fe40eb8dd2597956cae27d6fb02ac},
  journal = {Journal of Information Science},
  pages = 016555150607808,
  publisher = {CILIP},
  title = {{The folksonomy tag cloud: When is it useful?}},
  year = 2007
}

@inproceedings{hotho2006information,
  address = {Budva, Montenegro},
  author = {Hotho, Andreas and Jäschke, Robert and Schmitz, Christoph and Stumme, Gerd},
  booktitle = {Proceedings of the 3rd European Semantic Web Conference },
  interhash = {10ec64d80b0ac085328a953bb494fb89},
  intrahash = {7da1127fc4836e2cf58e3073f1b888b2},
  isbn = {3-540-34544-2},
  month = {June},
  pages = {411-426},
  publisher = {Springer},
  series = {LNCS},
  title = {Information Retrieval in Folksonomies: Search and Ranking},
  url = {http://www.kde.cs.uni-kassel.de/hotho/pub/2006/seach2006hotho_eswc.pdf},
  vgwort = {29},
  volume = 4011,
  year = 2006
}

@article{kleinberg1999hits,
  abstract = {. The network structure of a hyperlinked environment can be a rich source of information about the content of the environment, provided we have effective means for understanding it. We develop a set of algorithmic tools for extracting information from the link structures of such environments, and report on experiments that demonstrate their effectiveness in a variety of contexts on the World Wide Web. The central issue we address within our framework is the distillation of broad search topics,...},
  author = {Kleinberg, Jon M.},
  citeulike-article-id = {1115},
  comment = {HITS algorithm},
  interhash = {48a48add3cba613f07df1e9b56278b85},
  intrahash = {c86549355475331f563d0a3ba7816dab},
  journal = {Journal of the ACM},
  number = 5,
  pages = {604--632},
  priority = {1},
  title = {Authoritative sources in a hyperlinked environment},
  url = {http://citeseer.ist.psu.edu/kleinberg99authoritative.html},
  volume = 46,
  year = 1999
}

@inproceedings{Pageetal98,
  address = {Brisbane, Australia},
  author = {Page, L. and Brin, S. and Motwani, R. and Winograd, T.},
  booktitle = {Proceedings of the 7th International World Wide Web Conference},
  interhash = {ca10cf0b0dd668c64b1f378ff0775849},
  intrahash = {ac49c33e114ca171db40cece6a0ae4d6},
  pages = {161--172},
  title = {The PageRank citation ranking: Bringing order to the Web},
  url = {citeseer.nj.nec.com/page98pagerank.html},
  year = 1998
}

@inproceedings{breese98empirical,
  author = {Breese, John S. and Heckerman, David and Kadie, Carl},
  booktitle = {Proceedings of the 14$^{th}$ Conference on Uncertainty in Artificial Intelligence},
  interhash = {593f72dfa20e4b7b5b16205479989020},
  intrahash = {82cd7b6c312f4181b1d05adb10c1d56a},
  pages = {43-52},
  title = {Empirical Analysis of Predictive Algorithms for Collaborative Filtering},
  year = 1998
}