• Adriaans P and Zantinge D (1996) Data Mining. Addison Wesley Longman Ltd, Harlow, England.

  Google Scholar 

• Boykov Y and Huttenlocher D (1999) A new Bayesian framework for object recognition. In: proceedings of the IEEE Computer Society Conference on Computer Vision and Pattern Recognition. IEEE Computer Society.

• Bookstein A and Klein ST (1990) Information retrieval tools for literary analysis. In: Tjoa AM, Ed., Database and Expert Systems Applications. Springer-Verlag, Vienna, pp. 1–7.

  Google Scholar 

• Bookstein A and Klein ST (1991) Compression of correlated bit-vectors. Information Systems, 16:387–400.

  Google Scholar 

• Bookstein A, Klein ST and Raita T (1998) Clumping properties of content-bearing words. Journal of the American Society for Information Science, 49:102–114.

  Google Scholar 

• Bookstein A, Klein ST and Raita T (2001) Fuzzy hamming distance: A new dissimilarity measure. In: Amir, Amihood and Landau, G Eds., Proceedings: 12th Annual Symposium on Combinatorial Pattern Matching (CPM2001). Jerusalem, Israel, 1-4 July, 2001.

• Chang P and Krumm J (1999) Object recognition with color cooccurrence histograms. In: proceedings of the IEEE Computer Society Conference on Computer Vision and Pattern Recognition. IEEE Computer Society.

• Cormen TH, Leiserson CE and Rivest RL (1990) Introduction to Algorithms. MIT Press, Cambridge, MA.

  Google Scholar 

• Crochemore M and Rytter W (1994) Text Algorithms. Oxford University Press, New York.

  Google Scholar 

• Doyle L (1961) Semantic road maps for literature searchers. Journal of the ACM, 8(4):553–578.

  Google Scholar 

• Hamming RW (1980) Coding and Information Theory. Prentice-Hall, Englewood Cliffs, NJ.

  Google Scholar 

• Hearst MA (1994) Multi-paragraph segmentation of expository text. In: proc. ACL Conf. Las Cruces.

• Hearst MA and Plaunt C (1993) Subtopic structuring for full-length document access. In: proc. 16-th ACM-SIGIR Conf. Pittsburgh, pp. 59–68.

• Jansen BJ, Spink A, Bateman J and Saracevic T (1998) Real life information retrieval: A study of user queries on the web. SIGIR Forum, 32(1):5–18.

  Google Scholar 

• Knuth DE (1973) The Art of Computer Programming, Vol I, Fundamental Algorithms, Addison-Wesley, Reading, MA.

  Google Scholar 

• Kulyukin V and Burke A (in press) Mining free text for structure. In: wang J, Ed., Data Mining: Opportunities and Challenges, Idea Group Publishing, Pensylvania.

• Kulyukin V and Morley N (2002) Integrated object recognition in the three-tiered robot architecture, In: Proc. of the International Conference on Artificial Intelligence, Las Vegas.

• Kulyukin V and Zoko A (2000) Hamming distance for object recognition by mobile robots. In: Proceedings of the Research Symposium of the DePaul University School of Computer Science, Telecommunications and Information Systems (CTIRS-2000). DePaul University.

• Murphy R (2000) AI Robotics. MIT Press, New York.

  Google Scholar 

• Parker, JR (1993) Practical Computer Vision Using C. John Wiley and Sons, New York.

  Google Scholar 

• Roman S (1992) Coding and Information Theory. Springer-Verlag, New York.

  Google Scholar 

• Sankoff D and Kruskal JB (1983) Time Warps, String Edits, and Macromolecules: The Theory and Practice of Sequence Comparison. Addison-Wesley, Reading, MA.

  Google Scholar 

• Swain MJ and Ballard DH (1991) Color Indexing. International Journal of Computer Vision, 7:11–32.

  Google Scholar 

• Tam AM and Leung CHC (2001) Structured natural-language descriptions for semantic content retrieval of visual materials. Journal of the American Society for Information Science and Technology, 52(11):930–937.

  Google Scholar 

• Witten IH, Moffat A and Bell TC (1999) Managing Gigbytes. Morgan Kaufmann Publishers, San Fransisco.

  Google Scholar 

• Young SS, Scott PD and Nasrabadi N (1994) Multi-layer hopfield neural network. In: Proceedings of the IEEE Computer Society Conference on Computer Vision and Pattern Recogntion. IEEE Computer Society.

Download references