Learning of formal graph systems and its application to graph mining
Project/Area Number |
26280087
|
Research Category |
Grant-in-Aid for Scientific Research (B)
|
Allocation Type | Partial Multi-year Fund |
Section | 一般 |
Research Field |
Intelligent informatics
|
Research Institution | Kyushu International University |
Principal Investigator |
|
Co-Investigator(Kenkyū-buntansha) |
内田 智之 広島市立大学, 情報科学研究科, 准教授 (70264934)
松本 哲志 東海大学, 理学部, 准教授 (30307235)
鈴木 祐介 広島市立大学, 情報科学研究科, 助教 (10398464)
|
Project Period (FY) |
2014-04-01 – 2017-03-31
|
Project Status |
Completed (Fiscal Year 2016)
|
Budget Amount *help |
¥6,630,000 (Direct Cost: ¥5,100,000、Indirect Cost: ¥1,530,000)
Fiscal Year 2016: ¥1,950,000 (Direct Cost: ¥1,500,000、Indirect Cost: ¥450,000)
Fiscal Year 2015: ¥1,950,000 (Direct Cost: ¥1,500,000、Indirect Cost: ¥450,000)
Fiscal Year 2014: ¥2,730,000 (Direct Cost: ¥2,100,000、Indirect Cost: ¥630,000)
|
Keywords | グラフ文法 / グラフパターン / 形式体系 / 計算論的学習 / 機械学習 / 帰納推論 / グラフマイニング / グラフアルゴリズム |
Outline of Final Research Achievements |
Formal graph system (FGS) is a logic program that deals with term graphs instead of the terms of first-order predicate logic. In this research, we have studied the polynomial-time learnability of graph patterns and formal graph systems in the frameworks of the PAC-learning, query-learning, and inductive inference models. In particular, we introduced the hierarchy of FGS that is defined by some numerical graph invariants and the parameters of logic programs. We showed that there exist formal graph systems in the hierarchy that are learnable in the PAC framework. Furthermore, we described how distributional learning techniques are applied to formal graph system (FGS) languages. We showed that the regular FGS languages of bounded degree with the 1-finite context property (1-FCP) and bounded treewidth property are learned from positive data and membership queries.
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Report
(4 results)
Research Products
(29 results)