REFERENCES
- D. Salomon, Variable-Length Codes for Data Compression. London: Springer-Verlag, 2007.
- D. A. Huffman, “A method for the construction of minimum-redundancy code,” in Proceedings of the IRE, Cambridge, 1952, pp. 1098–101.
- D. Salomon, Data Compression Book, 2nd ed. New York, NY: Springer-Verlag, 2000.
- P. Elias, “Universal codeword sets and representations of the integers,” IEEE Trans. Inf. Theory, Vol. 21, pp. 194–203, 1975.
- R. F. Rice, “Some practical universal noiseless coding techniques,” Jet Propulsion Lab., Pasadena, CA, Tech. Rep. 2, 1979.
- S. Domnic, and V. Glory, “Inverted file compression using EGC and FEGC,” in Proceedings of the International Conference on Communication, Computing and Security, Odisha, 2012, pp. 735–42.
- P. Chovanec, M. Kratky, and J. Walder, “Lossless R-tree compression using variable-length codes,” in Proceeding of the International Conference on Internet Technology and Secured Transactions, Ostrava, 2010, pp. 1–8.
- M. Kobayashi, and K. Takeda, “Information retrieval on the web,” ACM Comput. Surv., vol. 32, pp. 144–73, 2000.
- J. Walder, M. Kratky, and R. Baca, “Benchmarking coding algorithms for the R-tree compression,” in Proceedings of the 9th Annual International Workshop on Data Bases, Czech Republic, 2009, pp. 32–43.
- H. E. Williams, and J. Zobel, “Indexing and retrieval for genomic databases,” IEEE Trans. Knowl. Data Eng., Vol. 14, pp. 63–78, 2002.
- H. Samet, Foundations of Multidimensional and Metric Data Structures. San Francisco, CA: Morgan Kaufmann, 2006.
- A. Henrich, H. W. Six, and P. Widmayer, “The LSD tree: spatial access to multidimensional and non-point objects,” in Proceedings of the 15th International Conference on Very Large Data Bases, San Francisco, 1989, pp. 45–53.
- A. Guttman, “R-trees: A dynamic index structure for spatial searching,” in Proceedings of ACM International Conference on Management of Data, Boston, MA, 1984, pp. 47–57.
- T. Sellis, N. Roussopoulos, and C. Faloutsos, “The r+-tree: A dynamic index for multidimensional objects,” in Proceedings of Very Large Data Bases, Brighton, 1987, pp. 507–18.
- N. Beckmann, H. P. Kriegel, R. Schneider, and B. Seeger, “The Rtree: An efficient and robust access method for points and rectangles,” in Proceedings of the ACM International Conference on Management of Data, New York, NY, 1990, pp. 322–31.
- I. Kamel, and C. Faloutsos, “Hilbert r-tree: An improved r-tree using fractals,” in Proceedings of Very Large Data Bases, Santiago, 1994, pp. 500–9.
- K. Kim, S. K. Cha, and K. Kwon, “Optimizing multidimensional index trees for main memory access,” SIGMOD Rec., Vol. 30, pp. 139–50, 2001.
- J. Kim, S. Im, S.-W. Kang, C.-S. Hwang, and S. Lee, “SQR-tree: A spatial index using semi-quantized MBR compression scheme in R-tree,” J. Inf. Sci. Eng., Vol. 23, pp. 1541–63, 2007.
- S. W. Golomb, “Run length encoding,” IEEE Trans. Inf. Theory, Vol. 12, pp. 399–401, 1966.
- K. Somasundaram, and S. Domnic, “Extended golomb code for integer representation,” IEEE Trans. Multimedia, Vol. 9, pp. 239–46, 2007.
- N. R. Brisaboa, M. R. Luaces, G. Navarro, and D. Seco, “A fun application of compact data structures to indexing geographic data,” in Proceedings of 5th FUN, Berlin, 2010, pp. 77–88.
- TIGER Dataset, Available: http://www.census.gov/geo/www/tiger.