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Multi-structure information retrieval method based on transformation invariance

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Abstract

The needs of efficient and flexible information retrieval on multi-structural data stored in database and network are significantly growing. Especially, its flexibility plays one of the key roles to acquire relevant information desired by users in retrieval process. However, most of the existing approaches are dedicated to a single content and data structure respectively, e.g., relational database and natural text. In this work, we propose “Multi-Structure Information Retrieval” (MSIR) approach applicable to various types of contents and data structures by adapting a small part of the approach to data structures. The power of this approach comes from the use of the invariant feature information obtained from byte patterns in the files through some mathematical transformation. The experimental evaluation of the proposed approach for both artificial and real data indicates its high feasibility.

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References

  1. Aho, V.R., Ethi, R. and Ullman, D.J.,Compilers: Principles, Techniques and Tools, Addison-Wesley, 1986.

  2. Baeza-Yates, R.A., “String Searching Algorithms,”Information Retrieval, Data Structures & Algorithms, (Baeza-Yates, R.A., Ed.), Chapter 10, pp. 219–240, 1992.

  3. Faloutsos, C., Equitz, W., Flickner, M., Niblack, W., Petkovic, D. and Barber, R., “Efficient and Effective Querying by Image Content,”Journal of Intelligence Information Systems, 3, 3/4, pp. 231–262, 1994.

    Article  Google Scholar 

  4. Faloutsos, C., “Signature Files,”Information Retrieval, Data Structures & Algorithms, (Baeza-Yates, R.A., Ed.), Chapter 4, pp. 44–65, 1992.

  5. Fox, C., “Lexical Analysis and Stoplists,”Information Retrieval, Data Structures & Algorithms, (Baeza-Yates, R.A., Ed.), Chapter 7, pp. 102–130, 1992.

  6. Fujimoto, A., Adachi, F., Washio, T., Motoda, H., Niwa, Y. and Hanafusa, H., “Expansion of Generic Search Method for Two-dimensional Data,”Proc. of the 17th Annual Conference of Japanese Soeiety for Artificial Intelligence (JSAI), 2C3-01, 2003. (in Japanese)

  7. Harman, D., Fox, E. and Baeza-Yates, R.A., “Inverted Files,”Information Retrieval, Data Structures & Algorithms, (Baeza-Yates, R.A., Ed.), Chapter 3, pp. 28–43, 1992.

  8. http://chasen.aist-nara.ac.jp/

  9. http://www.namazu.org/

  10. Manjunath, B. and Ma, W., “Texture Features for Browsing and Retrieval of Image Data,”IEEE Transactions on Pattern Analysis and Machine Intelligence, 18, 8 (August), pp. 837–842, 1996.

    Article  Google Scholar 

  11. Masui, T., “A Retrieval System Based on Signature Files Approach,”Monthly UNIX Magazine, Nov. 1999, ASCII, pp. 170–176, 1999. (in Japanese).

  12. Ogle, V.E. and Stonebraker, M., “Chabot: Retrieval from a Relational Database of Images,”IEEE Computer, 28, 9, pp. 1–18, 1995.

    Google Scholar 

  13. Pass, G., Zabih, R. and Miller, J., “Comparing Images Using Color Coherence Vectors,”Proc. of ACM Multimedia, 96, pp. 65–73, 1996.

    Google Scholar 

  14. Picrd, R., “A Society of Models for Video and Image Libraries,”Technical Report, 360, MIT Media Laboratory Perceptual Computing, 1996.

  15. Salton, G. and McGill, M. J.,Introduction to Modern Information Retrieval, McGraw-Hill Book Company, 1983.

  16. Swain, M. and Balland, D., “Color Indexing,”Int. Journ. Comput. Vis., 7, 1, pp. 11–32, 1991.

    Article  Google Scholar 

  17. The Institute of Electronics, Information and Communication Engineers (IEICE),Digital Signal Processing 10th Ed., Gihoudou, pp. 49–61, 1983. (in Japanese)

  18. Wang, J. and Acharya, R., “A Vertex Based Shape Coding Approach for Similar Shape Retrieval,”ACM Symposium on Applied Computing, Atlanta, pp. 520–524, 1998.

  19. Wang, J. and Acharya, R., “Efficient Access and Retrieval from a Shape Image Database,”IEEE Workshop on Content Based Access of Image and Video Libraries (CBAIL 98), Santa Barbara, 1998.

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Authors and Affiliations

  1. ISIR, Osaka University, 8-1 Mihogaoka, 567-0047, Ibaraki-shi, Osaka, Japan

    Fuminori Adachi, Takashi Washio, Atsushi Fujimoto & Hiroshi Motoda

  2. The Kansai Electric Power Co., Inc., 3-6-16, Nakano-shima, Kita-ku, Osaka-shi, Osaka, 530-8270, Japan

    Hidemitsu Hanafusa

Authors
  1. Fuminori Adachi
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  2. Takashi Washio
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  3. Atsushi Fujimoto
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  4. Hiroshi Motoda
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  5. Hidemitsu Hanafusa
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Corresponding author

Correspondence to Fuminori Adachi.

Additional information

Fuminori Adachi: He received his Master of engineering from Osaka University in ’03. He is enrolled in the doctoral course of Osaka University from ’03. His current research interest includes scientific discovery, data mining and machine learning techniques.

Takashi Washio, Ph.D.: He received his Ph.D. from Tohoku University in ’88. In ’88, he became a visiting reseacher in Massachusetts Institute of Technology. In ’90, he joined Mitsubishi Research Institute Inc., and is working for Osaka University from ’96. His current research interest includes scientific discovery, data mining and machine learning techniques.

Atsushi Fujimoto: He is enrolled in the master cource of Osaka University from ’03. His Current research interest includes correlation analysis, data mining and machine learning techniques.

Hiroshi Motoda, Ph.D.: He received his Ph.D. from University of Tokyo in ’72. In ’67, he joined Hitachi Ltd. and has been working for Osaka University since ’96. His current research interest includes scientific discovery, data mining and machine learning.

Hidemitsu Hanafusa: He received Master of Engineering from Keio University in ’83. In ’83, he joined The Kansai Electric Power Co. Ins. (KEPCO). He researched on Maintenance Support System at INSS from ’97 to ’02. Now, he is working in KEPCO.

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Adachi, F., Washio, T., Fujimoto, A. et al. Multi-structure information retrieval method based on transformation invariance. New Gener Comput 23, 291–313 (2005). https://doi.org/10.1007/BF03037635

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  • DOI: https://doi.org/10.1007/BF03037635

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