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Titlebook: Discovery Science; Third International Setsuo Arikawa,Shinichi Morishita Conference proceedings 2000 Springer-Verlag Berlin Heidelberg 200

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發(fā)表于 2025-3-26 21:26:06 | 只看該作者
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發(fā)表于 2025-3-27 01:09:36 | 只看該作者
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發(fā)表于 2025-3-27 07:05:14 | 只看該作者
A Unifying Approach to HTML Wrapper Representation and Learningn. This calls for representation formalisms that match the World Wide Web reality and for learning approaches and learnability results that apply to these formalisms..The concept of elementary formal systems is appropriately generalized to allow for the representation of wrapper classes which are re
34#
發(fā)表于 2025-3-27 09:57:33 | 只看該作者
Discovery of Web Communities Based on the Co-occurrence of Referenceson interest. Discovery of such community is expected to assist users’ information retrieval from theWeb. The method proposed in this paper is based on the assumption that hyperlinks to related Web pages often co-occur. Relations of Web pages are detected by the co-occurrence of hyperlinks on the pag
35#
發(fā)表于 2025-3-27 14:28:20 | 只看該作者
Clustering and Visualization of Large Protein Sequence Databases by Means of an Extension of the Selelf-Organizing Map (SOM) is used in this work for the clustering of all the 77,977 protein sequences of the SWISS-PROT database, release 37. In this method, unlike in some previous ones, the data sequences are not converted into histogram vectors in order to perform the clustering. Instead, a collec
36#
發(fā)表于 2025-3-27 19:03:08 | 只看該作者
A Simple Greedy Algorithm for Finding Functional Relations: Efficient Implementation and Average Casare represented in the form of tables and many rules are represented in the form of functions. A simple greedy algorithm has been known as an approximation algorithm for this problem. In this algorithm, the original problem is reduced to the set cover problem and a well-known greedy algorithm for th
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發(fā)表于 2025-3-28 00:13:52 | 只看該作者
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發(fā)表于 2025-3-28 09:22:18 | 只看該作者
Classifying Scenarios using Belief Decision Trees decision tree technique and the belief function theory as understood in the transferable belief model in order to find the classes of the scenarios (of a given problem) that may happen in the future. Two major phases will be ensured: the construction of the belief decision tree representing the sce
40#
發(fā)表于 2025-3-28 13:49:36 | 只看該作者
A Practical Algorithm to Find the Best Subsequence Patternswn to be NP-complete.We generalize the problem to an optimization problem, and give a practical algorithm to solve it exactly. Our algorithm uses pruning heuristic and subsequence automata, and can find the best subsequence. We show some experiments, that convinced us the approach is quite promising
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