Machine learning theory for graph pattern languages and its applications to graph mining
| Project/Area Number |
20500016
|
|---|
| Research Category |
Grant-in-Aid for Scientific Research (C)
|
| Allocation Type | Single-year Grants |
|---|
| Section | 一般 |
|---|
| Research Field |
Fundamental theory of informatics
|
|---|
| Research Institution | Kyushu University |
|---|
Principal Investigator |
SHOUDAI Takayoshi Kyushu University, システム情報科学研究院, 准教授 (50226304)
|
|---|
| Co-Investigator(Kenkyū-buntansha) |
UCHIDA Tomoyuki 広島市立大学, 情報科学研究科, 准教授 (70264934)
|
|---|
| Co-Investigator(Renkei-kenkyūsha) |
SUZUKI Yusuke 広島市立大学, 情報科学研究科, 助教 (10398464)
MATSUMOTO Satoshi 東海大学, 理学部, 准教授 (30307235)
|
|---|
| Project Period (FY) |
2008 – 2010
|
| Project Status |
Completed (Fiscal Year 2010)
|
| Budget Amount *help |
¥4,550,000 (Direct Cost: ¥3,500,000、Indirect Cost: ¥1,050,000)
Fiscal Year 2010: ¥1,430,000 (Direct Cost: ¥1,100,000、Indirect Cost: ¥330,000)
Fiscal Year 2009: ¥1,430,000 (Direct Cost: ¥1,100,000、Indirect Cost: ¥330,000)
Fiscal Year 2008: ¥1,690,000 (Direct Cost: ¥1,300,000、Indirect Cost: ¥390,000)
|
|---|
| Keywords | 計算論的学習理論 / 知識発見とデータマイニング / グラフアルゴリズム / グラフパターン / グラフ言語 / グラフ構造データ / データマイニング / 機械学習 / 機械発見 / 帰納推論 |
|---|
| Research Abstract |
We proposed a series of techniques for extracting graph-structured patterns efficiently from graph-structured data, such as chemical compound data, HTML/XML data, network traffic data, and so on. In order to design expressive graph-structured patterns, we focused on tree-like properties (e. g., outerplanarity, tree-width) of target data. Our proposed algorithms run efficiently on real data, and discovered a number of interesting graph-structured patterns.
|
Report
(4 results)
Research Products
(35 results)
