@article{Hoonlor:2013:TCS:2507771.2500892,
  abstract = {Keywords in the ACM Digital Library and IEEE Xplore digital library and in NSF grants anticipate future CS research.},
  acmid = {2500892},
  address = {New York, NY, USA},
  author = {Hoonlor, Apirak and Szymanski, Boleslaw K. and Zaki, Mohammed J.},
  doi = {10.1145/2500892},
  interhash = {425133ebceab2bce5f418ffd9917df55},
  intrahash = {4a2aee492bfcfcdbbcc7774bdcddd4a2},
  issn = {0001-0782},
  issue_date = {October 2013},
  journal = {Commun. ACM},
  month = oct,
  number = 10,
  numpages = {10},
  pages = {74--83},
  publisher = {ACM},
  title = {Trends in Computer Science Research},
  url = {http://doi.acm.org/10.1145/2500892},
  volume = 56,
  year = 2013
}

@inproceedings{PuWang:2007,
  abstract = {The exponential growth of text documents available on the Internet has created an urgent need for accurate, fast, and general purpose text classification algorithms. However, the "bag of words" representation used for these classification methods is often unsatisfactory as it ignores relationships between important terms that do not co-occur literally. In order to deal with this problem, we integrate background knowledge - in our application: Wikipedia - into the process of classifying text documents. The experimental evaluation on Reuters newsfeeds and several other corpus shows that our classification results with encyclopedia knowledge are much better than the baseline "bag of words " methods.},
  author = {Wang, Pu and Hu, Jian and Zeng, Hua-Jun and Chen, Lijun and Chen, Zheng},
  booktitle = {Data Mining, 2007. ICDM 2007. Seventh IEEE International Conference on},
  doi = {10.1109/ICDM.2007.77},
  interhash = {8a899b60047e20e162fc12b2ff6f8142},
  intrahash = {66058efbca5abd1222f72c32365d23fa},
  isbn = {978-0-7695-3018-5},
  issn = {1550-4786},
  pages = {332-341},
  title = {Improving Text Classification by Using Encyclopedia Knowledge},
  url = {ftp://ftp.computer.org/press/outgoing/proceedings/icdm07/Data/3018a332.pdf},
  year = 2007
}

@misc{voss-2007,
  abstract = {This paper gives an overview of current trends in manual indexing on the Web. Along with a general rise of user generated content there are more and more tagging systems that allow users to annotate digital resources with tags (keywords) and share their annotations with other users. Tagging is frequently seen in contrast to traditional knowledge organization systems or as something completely new. This paper shows that tagging should better be seen as a popular form of manual indexing on the Web. Difference between controlled and free indexing blurs with sufficient feedback mechanisms. A revised typology of tagging systems is presented that includes different user roles and knowledge organization systems with hierarchical relationships and vocabulary control. A detailed bibliography of current research in collaborative tagging is included.},
  author = {Voss, Jakob},
  interhash = {c293cd6ef590c6aaf32df75cbdb9de82},
  intrahash = {9ec98351dc630ea6b1f65046ba44a8dd},
  title = {Tagging, Folksonomy \& Co - Renaissance of Manual Indexing?},
  url = {http://www.citebase.org/abstract?id=oai:arXiv.org:cs/0701072},
  year = 2007
}

@misc{eigenvector2005Langville,
  abstract = {Web information retrieval is significantly more challenging than traditional well-controlled,
small document collection information retrieval. One main difference between traditional
information retrieval and Web information retrieval is the Web’s hyperlink structure. This
structure has been exploited by several of today’s leading Web search engines, particularly
Google and Teoma. In this survey paper, we focus on Web information retrieval methods
that use eigenvector computations, presenting the three popular methods of HITS,
PageRank, and SALSA.},
  author = {Langville, Amy N. and Meyer, Carl D.},
  interhash = {d457071e1f5270c3d50cbb3243546833},
  intrahash = {445172dea700200486177842e9dfe3cb},
  journal = {The SIAM Review},
  number = 1,
  pages = {135-161},
  title = {A Survey of Eigenvector Methods of Web Information Retrieval},
  url = {http://www.cofc.edu/~langvillea/surveyEVwebIRReprint.pdf},
  volume = 47,
  year = 2005
}

@inbook{kleinberg2006temporal,
  author = {Kleinberg, J.},
  booktitle = {Data Stream Management: Processing High-Speed Data Streams},
  editor = {Garofalakis, M. and Gehrke, J. and Rastogi, R.},
  interhash = {85abe180184277c0396745c7ce050c98},
  intrahash = {9c57003d80b81eab2f66b2faf02acb27},
  isbn = {3540286071},
  publisher = {Springer},
  title = {Temporal Dynamics of On-Line Information Streams},
  url = {http://www.cs.cornell.edu/home/kleinber/stream-survey04.pdf},
  year = 2006
}