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Self-Organizing Map and Hidden Markov Model for Data Set Generation

p. 319-332

Abstract

We focus on sequences of the data of which a user selects from a multimedia database. These data cannot be stereotyped because user's view for them changes by each user. Therefore, we represent the structure of the multimedia database as the vector representing both user's view and the stereotyped vector. Such a vector can be classified by SOM (Self-Organizing Map). On the other hand, we introduce a technique for data set generation. If such a set consists of sequences of data, Hidden Markov Model (HMM) will be available for practical purposes. Therefore, we introduce HMM and Vector-state Markov Model (VMM) to represent the vector of user's view, and to acquire the sequence containing the change of user's view. Lastly, we will refer to an extended technique for an interactive system using the rough set theory.

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References

Bibliographical reference

Tadashi Ae and Kazaumasa Kioi, « Self-Organizing Map and Hidden Markov Model for Data Set Generation », CASYS, 20 | 2008, 319-332.

Electronic reference

Tadashi Ae and Kazaumasa Kioi, « Self-Organizing Map and Hidden Markov Model for Data Set Generation », CASYS [Online], 20 | 2008, Online since 08 October 2024, connection on 27 December 2024. URL : http://popups.uliege.be/3041-539x/index.php?id=2937

Authors

Tadashi Ae

Hiroshima Institute of Technology, 2-1-1 Miyake, Saeki-ku, Hiroshima, 731-5193 Japan

By this author

Kazaumasa Kioi

Hiroshima Institute of Technology, 2-1-1 Miyake, Saeki-ku, Hiroshima, 731-5193 Japan

Copyright

CC BY-SA 4.0 Deed