Learning of Finite Unions of Tree Patterns with Repeated Internal Structured Variables from Queries

• Matsumoto Satoshi

  Tokai University

• Suzuki Yusuke

  Hiroshima City University

• Shoudai Takayoshi

  Kyushu University

• Miyahara Tetsuhiro

  Hiroshima City University

• Uchida Tomoyuki

  Hiroshima City University

抄録

The exact learning model by Angluin (1988) is a mathematical model of learning via queries in computational learning theory. A term tree is a tree pattern consisting of ordered tree structures and repeated structured variables, which occur more than once. Thus, a term tree is suited for representing common tree structures based on tree-structured data, such as HTML and XML files on the Web. In this paper, we consider the learnability of finite unions of term trees with repeated variables in the exact learning model. We present polynomial time learning algorithms for finite unions of term trees with repeated variables by using superset and restricted equivalence queries. Moreover, we show that there exists no polynomial time learning algorithm for finite unions of term trees by using restricted equivalence, membership, and subset queries. This result indicates the hardness of learning finite unions of term trees in the exact learning model.

収録刊行物

• IPSJ Online Transactions

  IPSJ Online Transactions 2 250-260, 2009

  一般社団法人 情報処理学会

キーワード

• General Computer Science

詳細情報

• CRID: 1390001205294832000
• NII論文ID: 130000142338
• DOI: 10.2197/ipsjtrans.2.250
• ISSN: 18826660
• Web Site: http://www.jstage.jst.go.jp/article/ipsjtrans/2/0/2_0_250/_pdf
• 本文言語コード: en
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