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Titlebook: Knowledge Discovery, Knowledge Engineering and Knowledge Management; First International Ana Fred,Jan L. G. Dietz,Joaquim Filipe Conferenc

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樓主: 故障
11#
發(fā)表于 2025-3-23 10:31:42 | 只看該作者
12#
發(fā)表于 2025-3-23 17:46:02 | 只看該作者
Sequential Supervised Learning for Hypernym Discovery from Wikipedian extraction, online encyclopedias provide far more structuredness and reliability. In this paper we propose a novel approach that combines syntactic and lexical-semantic information to identify hypernymic relationships. We compiled semi-automatically and manually created training data and a gold st
13#
發(fā)表于 2025-3-23 20:16:12 | 只看該作者
Evolving Estimators for Software Project Developmentthe authors examine a genetic programming system for symbolic regression; the main goal is to derive equations for estimating the development effort that are highly accurate. These mathematical formulas are expected to reveal relationships between the available input features and the estimated proje
14#
發(fā)表于 2025-3-23 23:20:34 | 只看該作者
Extracting and Rendering Representative Sequencesmallest possible number of representative sequences that ensure a given coverage of the whole set, i.e. that have together a given percentage of sequences in their neighbourhood. The proposed heuristic for extracting the representative subset requires as main arguments a pairwise distance matrix, a
15#
發(fā)表于 2025-3-24 03:26:26 | 只看該作者
Unsupervised Quadratic Discriminant Embeddings Using Gaussian Mixture Modelsposed here, called the ., is an unsupervised dimension reduction method that relies on the estimation of a Gaussian Mixture Model (GMM) parameters. This allows to capture information not only among data points, but also among clusters in the same embedding space. Points are represented in the cluste
16#
發(fā)表于 2025-3-24 10:31:55 | 只看該作者
17#
發(fā)表于 2025-3-24 13:50:10 | 只看該作者
Average Cluster Consistency for Cluster Ensemble Selectione robust partition of the data. However, the existence of many approaches leads to another problem which consists in knowing which of these approaches to produce the cluster ensembles’ data and to combine these partitions best fits a given data set. In this paper, we propose a new measure to select
18#
發(fā)表于 2025-3-24 16:26:23 | 只看該作者
19#
發(fā)表于 2025-3-24 19:35:31 | 只看該作者
Towards a Formalization of Ontology Relations in the Context of Ontology Repositoriess paper, we describe DOOR - The .escriptive .ntology of .ntology .elations, to represent, manipulate and reason upon relations between ontologies in large ontology repositories. DOOR represents a first attempt in describing and formalizing ontology relations. In fact, it does not pretend to be a uni
20#
發(fā)表于 2025-3-25 00:23:24 | 只看該作者
ARAGOG Semantic Search Engine: Working, Implementation and Comparison with Keyword-Based Search Engio cope up with this fast pace of data generation effectively in future. Giving relevant, useful and close to accurate search results will be a big challenge given their current design and approach. Search Engines will be required to make a transit from keyword based search approach to semantic based
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