Fundamental algorithms for detecting music similarities from various viewpoints
| Project/Area Number |
26330243
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| Research Category |
Grant-in-Aid for Scientific Research (C)
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| Allocation Type | Multi-year Fund |
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| Section | 一般 |
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| Research Field |
Intelligent informatics
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| Research Institution | Hokkaido University |
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Principal Investigator |
OKUBO Yoshiaki 北海道大学, 情報科学研究科, 助教 (40271639)
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| Project Period (FY) |
2014-04-01 – 2017-03-31
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| Project Status |
Completed (Fiscal Year 2016)
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| Budget Amount *help |
¥4,420,000 (Direct Cost: ¥3,400,000、Indirect Cost: ¥1,020,000)
Fiscal Year 2016: ¥1,300,000 (Direct Cost: ¥1,000,000、Indirect Cost: ¥300,000)
Fiscal Year 2015: ¥1,430,000 (Direct Cost: ¥1,100,000、Indirect Cost: ¥330,000)
Fiscal Year 2014: ¥1,690,000 (Direct Cost: ¥1,300,000、Indirect Cost: ¥390,000)
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| Keywords | 楽曲類似検索 / クラスタ / 形式概念分析 / 疑似クリーク / 分類問題 / クラス分類 / k-近傍 / 多段多数決 / クリーク探索 / 次元圧縮 / 非負値行列因子分解 / 類似楽曲検索 / Top-N 極大 k-plex 抽出 / 真 k-plex 性 / 頻出長大パターン / 極大 k-plex |
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| Outline of Final Research Achievements |
The purpose of this research is to investigate methods for flexible and useful Music Information Retrieval. Especially, we have tried to formalize several fundamental methods for observing and analyzing similar music from various viewpoints. The algorithms we have developed based on Pattern Mining (Formal Concept Analysis) and Dense-Subgraph Discovery are 1) Algorithm for similar music retrieval based on colossal frequent patterns, and 2) Algorithm for extracting Top-N largest dense subgraphs based on proper k-plex search. Furthermore, we also have developed 3) Classification algorithm with label modification based on multiple majority votes, and 4) Classification algorithm with dimension reduction based on class-label information.
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Report
(4 results)
Research Products
(15 results)
