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Titlebook: Knowledge Management in Organizations; 14th International C Lorna Uden,I-Hsien Ting,Juan Manuel Corchado Conference proceedings 2019 Spring

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21#
發(fā)表于 2025-3-25 05:53:56 | 只看該作者
22#
發(fā)表于 2025-3-25 11:25:57 | 只看該作者
Scientometric Analysis of Knowledge in the Context of Project Managementild a detailed state of the art about the matter of study, allowing the identification of main elements investigated on the scientific literature about the knowledge on this context. Firstly; a theoretical framework was build, allowing the identification of concepts about knowledge management and sc
23#
發(fā)表于 2025-3-25 13:04:02 | 只看該作者
24#
發(fā)表于 2025-3-25 16:54:11 | 只看該作者
Entrepreneurship Knowledge Insights in Emerging Markets Using a SECI Model Approachwhere the relative cost of failure is even higher than in develop countries. There is little specific Latin American knowledge that has been incorporated to help reducing this failure rate, most of the entrepreneurial models have been developed for economies with advanced entrepreneurial ecosystems
25#
發(fā)表于 2025-3-25 19:58:44 | 只看該作者
26#
發(fā)表于 2025-3-26 02:44:44 | 只看該作者
Automatic Sleep Staging Based on Deep Neural Network Using Single Channel EEGsSleepNet, using raw single-channel EEG signals. Most of the existing studies utilize hand-engineered features to identify sleep stages. These methods may ignore some important features of the signals, and then influence the effect of sleep stage classification. Instead of hand-engineering features,
27#
發(fā)表于 2025-3-26 04:39:29 | 只看該作者
Evolving Fuzzy Membership Functions for Soft Skills Assessment Optimizationcandidates. This paper is part of an ongoing research in the field of PhD profiling. The novelty here is an evolutionary fuzzy model, based on the Membership Functions (MFs) optimization, used to obtain the soft skills candidate profiles. The general aim of the project is the definition of a set of
28#
發(fā)表于 2025-3-26 11:08:13 | 只看該作者
Unsupervised Deep Clustering for Fashion Imagesd and semi-structured data. In this paper, we propose a fashion image deep clustering (FiDC) model which includes two parts, feature representation and clustering. The fashion images are used as the input and are processed by a deep stacked autoencoder to produce latent feature representation, and t
29#
發(fā)表于 2025-3-26 13:31:41 | 只看該作者
30#
發(fā)表于 2025-3-26 18:35:17 | 只看該作者
Discovering Emerging Research Topics Based on SPO Predicationsciently. To achieve this goal, we propose a percolation approach to discovering emerging research topics by combining text mining and scientometrics methods based on Subject-Predication-Object (SPO) predications, which consist of a subject argument, an object argument, and the relation that binds th
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