Stable Extraction of Frequent Sub-sequences from Sequential Symbol Input | Zendy

Kenta Morita | Zendy; Haruhiko Takase | Zendy; N. Morita | Zendy; Hiroharu Kawanaka | Zendy; Shinji Tsuruoka | Zendy

AI Assistant Blog Pricing

Home ZAIA Blog

Open Access

Stable Extraction of Frequent Sub-sequences from Sequential Symbol Input

Author(s) -

Kenta Morita,

Haruhiko Takase,

N. Morita,

Hiroharu Kawanaka,

Shinji Tsuruoka

Publication year - 2017

Publication title -

procedia computer science

Language(s) - English

Resource type - Journals

SCImago Journal Rank - 0.334

H-Index - 76

ISSN - 1877-0509

DOI - 10.1016/j.procs.2017.08.240

Subject(s) - computer science , focus (optics) , symbol (formal) , simple (philosophy) , sequence (biology) , plural , artificial intelligence , algorithm , pattern recognition (psychology) , data mining , philosophy , linguistics , physics , epistemology , biology , optics , genetics , programming language

In this paper, we discuss the method for stable extraction of frequent sub-sequences from symbols infused continuously. To make learning algorithm stably, we focus on two problems: the case where input data contain plural frequent sub-sequences and the case where appearance rate of frequent sub-sequences is low. To overcome these problems, we propose two ideas: new incremental structure and new learning rule. By simple experiments, we show the effectiveness of the proposed method.

The content you want is available to Zendy users.

Already have an account? Click here to sign in.

Having issues? You can contact us here

Accelerating Research