Presentation | 2003/3/6 Distributed Knowledge Discovery based on Merging Hypotheses Toshiyuki KIKUCHI, Akihiro YAMAMOTO, |
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Abstract(in Japanese) | (See Japanese page) |
Abstract(in English) | In this paper we propose a method for knowledge discovery from distributed data on distributed computers. Each of the computers is assumed to have a knowledge discovery system which searches hypotheses from general ones to specific ones. We also assume that each hypothesis can be represented as a logic program. Then the discovery method is to correct hypotheses generated by the computers and then merge them. For the merge of hypotheses we use the most general specialization of clauses. We also validate each clause in the merged hypotheses. We implement our method on the EVLD system, which we developed previously, and call it Distributed EVLD (Distributed EVLD). In the paper we report how our method works well with a well-known data set. |
Keyword(in Japanese) | (See Japanese page) |
Keyword(in English) | inductive logic programming / distributed processing / specialization |
Paper # | AI2002-64 |
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Committee | AI |
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Conference Date | 2003/3/6(1days) |
Place (in Japanese) | (See Japanese page) |
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Registration To | Artificial Intelligence and Knowledge-Based Processing (AI) |
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Language | JPN |
Title (in Japanese) | (See Japanese page) |
Sub Title (in Japanese) | (See Japanese page) |
Title (in English) | Distributed Knowledge Discovery based on Merging Hypotheses |
Sub Title (in English) | |
Keyword(1) | inductive logic programming |
Keyword(2) | distributed processing |
Keyword(3) | specialization |
1st Author's Name | Toshiyuki KIKUCHI |
1st Author's Affiliation | MemeMedia Laboratory, Hokkaido University() |
2nd Author's Name | Akihiro YAMAMOTO |
2nd Author's Affiliation | MemeMedia Laboratory, Hokkaido University |
Date | 2003/3/6 |
Paper # | AI2002-64 |
Volume (vol) | vol.102 |
Number (no) | 709 |
Page | pp.pp.- |
#Pages | 6 |
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