References and Resources

Print and Online References

• Baeza-Yates, R., and B. Ribeiro-Neto (1999). Modern Information Retrieval. New York: ACM Press.
  
• Berry, M. W. (Ed.) (2001). Computational Information Retrieval, Proceedings of CIR'00, Philadelphia: SIAM.
  
• Berry, M. W., and M. Browne (1999). Understanding Search Engines: Mathematical Modeling and Text Retrieval. Philadelphia, PA: SIAM.
  
• Berry, M. W., Z. Drmac, and E. R. Jessup (1999). Matrices, Vector Spaces and Information Retrieval. SIAM Review 41:335-362.
  
• Berry, M. W., and G. W. O'Brien (1998). Using linear algebra for intelligent information retrieval. SIAM Review 37:573-595.
  
• Books in Print (2001). New York: R.R. Bowker.
  
• Bradley, P. (2003). Multi-search engines - a comparison. Web page: http://www.philb.com/msengine.htm. Accessed 10/28/05.
  
• Ding, C. H. Q. (1999). A similarity-based probability model for LSI. Proceedings of the 22nd ACM SIGIR `99 Conference, pp. 59-65.
  
• Dumais, S. T. (1991). Improving the retrieval of information from external sources. Behavior Research Methods, Instruments and Computers 23:229-236.
  
• Eckart, C., and G. Young (1936). The approximation of one matrix by another of lower rank. Psychometrika 1:211-218.
  
• Frakes, W. B., and R. Baeza-Yates (1992). Information Retrieval: Data Structures and Algorithms. Englewood Cliffs, NJ: Prentice Hall.
  
• Glossbrenner, A. and E. (2001). Search Engines for the World Wide Web. Berkeley, CA: Peachpit Press.
  
• Golub, G. H., and C. F. Van Loan (1996). Matrix Computations. Baltimore: Johns Hopkins University Press.
  
• Harman, D., and E. Voorhees (Eds.) (1996). Overview of the fifth Text REtrieval Conference (TREC-5). In Information Technology: The Fifth Text REtrieval Conference (TREC-5), Gaithersburg, MD: NIST, 500-238 (Nov.): 1-28.
  
• Jones, S. K. (1972). A statistical interpretation of term specificity and its applications in retrieval. J. Documentation 28:11-21.
  
• Jones, W., and G. Furnas (1987). Pictures of relevance: A geometric analysis of similarity measures. Journal of American Society for Information Retrieval 38:420-442.
  
• Korfhage, R. R. (1997). Information Storage and Retrieval. New York: Wiley Computer Publishing.
  
• Langville, A. N., and C. D. Meyer (2005). A survey of eigenvector methods for Web information retrieval. SIAM Review, 47(1):135-161.
  
• Langville, A. N., and C. D. Meyer (2006). Google's PageRank and Beyond: The Science of Search Engine Rankings. Princeton, NJ: Princeton University Press.
  
• Letsche, T. A., and M. W. Berry. (1997). Large-scale information retrieval with LSI. Informatics and Computer Science, 100:105-137.
  
• Lyman, P., and H. R. Varian (2000). How Much Information. Web page: http://www.sims.berkeley.edu/how-much-info. Accessed 10/28/05.
  
• Marchiori, M. (1997). The quest for correct information of the Web: hyper search engines. The Sixth International WWW Conference (WWW97). Santa Clara, USA, April 7-11.
  
• Medlars Collection (2002). Available at http://www.cs.utk.edu/~lsi/corpa.html. Accessed 10/28/05.
  
• Meyer, C.D. (2000). Matrix Analysis, Philadelphia: SIAM.
  
• Salton, G. (1971). The SMART Retrieval System: Experiments in Automatic Document Processing, New Jersey: Prentice Hall.
  
• Ulrich's International Periodicals Directory (2001). New York: R.R. Bowker.
  
• Wurman, R. (1989). Information Anxiety, New York: Doubleday.
  
• Zha, H., O. Marques, and H. Simon (1998). A subspace-based model for information retrieval with applications in latent semantic indexing. Proceedings of Irregular '98, Lecture Notes in Computer Science, 1457:29-42.
  
• Zha, H., and H. D. Simon (1999). On updating problems in latent semantic indexing. SIAM Journal on Scientific Computing, 21(2):782-791.
  

Online Resources

• About Online Business/Hosting,http://internet.about.com/cs/searchtechnology/
  
• Latent Semantic Indexing Web Site, http://www.cs.utk.edu/~lsi/
  
• Search Engine Guide,http://www.searchengineguide.com
  
• Search Engine Showdown,http://www.notess.com/search/
  
• Search Engine Watch,http://www.searchenginewatch.com